Merge branch 'main' into pr-1845

.gitignore

@@ -1,3 +1,4 @@
+.worktrees/
 .assets
 .env
 *.pyc
@@ -19,4 +20,5 @@ __pycache__/
 poetry.lock
 .pytest_cache/
 botpy.log
-tests/
+nano.*.save
+

README.md

@@ -12,17 +12,29 @@
   </p>
 </div>
 
-🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw) 
+🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw).
 
-⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.
+⚡️ Delivers core agent functionality with **99% fewer lines of code** than OpenClaw.
 
-📏 Real-time line count: **3,935 lines** (run `bash core_agent_lines.sh` to verify anytime)
+📏 Real-time line count: run `bash core_agent_lines.sh` to verify anytime.
 
 ## 📢 News
 
+- **2026-03-08** 🚀 Released **v0.1.4.post4** — a reliability-packed release with safer defaults, better multi-instance support, sturdier MCP, and major channel and provider improvements. Please see [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post4) for details.
+- **2026-03-07** 🚀 Azure OpenAI provider, WhatsApp media, QQ group chats, and more Telegram/Feishu polish.
+- **2026-03-06** 🪄 Lighter providers, smarter media handling, and sturdier memory and CLI compatibility.
+- **2026-03-05** ⚡️ Telegram draft streaming, MCP SSE support, and broader channel reliability fixes.
+- **2026-03-04** 🛠️ Dependency cleanup, safer file reads, and another round of test and Cron fixes.
+- **2026-03-03** 🧠 Cleaner user-message merging, safer multimodal saves, and stronger Cron guards.
+- **2026-03-02** 🛡️ Safer default access control, sturdier Cron reloads, and cleaner Matrix media handling.
+- **2026-03-01** 🌐 Web proxy support, smarter Cron reminders, and Feishu rich-text parsing improvements.
 - **2026-02-28** 🚀 Released **v0.1.4.post3** — cleaner context, hardened session history, and smarter agent. Please see [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post3) for details.
 - **2026-02-27** 🧠 Experimental thinking mode support, DingTalk media messages, Feishu and QQ channel fixes.
 - **2026-02-26** 🛡️ Session poisoning fix, WhatsApp dedup, Windows path guard, Mistral compatibility.
+
+<details>
+<summary>Earlier news</summary>
+
 - **2026-02-25** 🧹 New Matrix channel, cleaner session context, auto workspace template sync.
 - **2026-02-24** 🚀 Released **v0.1.4.post2** — a reliability-focused release with a redesigned heartbeat, prompt cache optimization, and hardened provider & channel stability. See [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post2) for details.
 - **2026-02-23** 🔧 Virtual tool-call heartbeat, prompt cache optimization, Slack mrkdwn fixes.
@@ -30,10 +42,6 @@
 - **2026-02-21** 🎉 Released **v0.1.4.post1** — new providers, media support across channels, and major stability improvements. See [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post1) for details.
 - **2026-02-20** 🐦 Feishu now receives multimodal files from users. More reliable memory under the hood.
 - **2026-02-19** ✨ Slack now sends files, Discord splits long messages, and subagents work in CLI mode.
-
-<details>
-<summary>Earlier news</summary>
-
 - **2026-02-18** ⚡️ nanobot now supports VolcEngine, MCP custom auth headers, and Anthropic prompt caching.
 - **2026-02-17** 🎉 Released **v0.1.4** — MCP support, progress streaming, new providers, and multiple channel improvements. Please see [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4) for details.
 - **2026-02-16** 🦞 nanobot now integrates a [ClawHub](https://clawhub.ai) skill — search and install public agent skills.
@@ -70,6 +78,25 @@
   <img src="nanobot_arch.png" alt="nanobot architecture" width="800">
 </p>
 
+## Table of Contents
+
+- [News](#-news)
+- [Key Features](#key-features-of-nanobot)
+- [Architecture](#️-architecture)
+- [Features](#-features)
+- [Install](#-install)
+- [Quick Start](#-quick-start)
+- [Chat Apps](#-chat-apps)
+- [Agent Social Network](#-agent-social-network)
+- [Configuration](#️-configuration)
+- [Multiple Instances](#-multiple-instances)
+- [CLI Reference](#-cli-reference)
+- [Docker](#-docker)
+- [Linux Service](#-linux-service)
+- [Project Structure](#-project-structure)
+- [Contribute & Roadmap](#-contribute--roadmap)
+- [Star History](#-star-history)
+
 ## ✨ Features
 
 <table align="center">
@@ -115,6 +142,29 @@ uv tool install nanobot-ai
 pip install nanobot-ai
 ```
 
+### Update to latest version
+
+**PyPI / pip**
+
+```bash
+pip install -U nanobot-ai
+nanobot --version
+```
+
+**uv**
+
+```bash
+uv tool upgrade nanobot-ai
+nanobot --version
+```
+
+**Using WhatsApp?** Rebuild the local bridge after upgrading:
+
+```bash
+rm -rf ~/.nanobot/bridge
+nanobot channels login
+```
+
 ## 🚀 Quick Start
 
 > [!TIP]
@@ -177,6 +227,7 @@ Connect nanobot to your favorite chat platform.
 | **Slack** | Bot token + App-Level token |
 | **Email** | IMAP/SMTP credentials |
 | **QQ** | App ID + App Secret |
+| **Wecom** | Bot ID + Bot Secret |
 
 <details>
 <summary><b>Telegram</b> (Recommended)</summary>
@@ -293,12 +344,18 @@ If you prefer to configure manually, add the following to `~/.nanobot/config.jso
     "discord": {
       "enabled": true,
       "token": "YOUR_BOT_TOKEN",
-      "allowFrom": ["YOUR_USER_ID"]
+      "allowFrom": ["YOUR_USER_ID"],
+      "groupPolicy": "mention"
     }
   }
 }
 ```
 
+> `groupPolicy` controls how the bot responds in group channels:
+> - `"mention"` (default) — Only respond when @mentioned
+> - `"open"` — Respond to all messages
+> DMs always respond when the sender is in `allowFrom`.
+
 **5. Invite the bot**
 - OAuth2 → URL Generator
 - Scopes: `bot`
@@ -361,7 +418,7 @@ pip install nanobot-ai[matrix]
 
 | Option | Description |
 |--------|-------------|
-| `allowFrom` | User IDs allowed to interact. Empty = all senders. |
+| `allowFrom` | User IDs allowed to interact. Empty denies all; use `["*"]` to allow everyone. |
 | `groupPolicy` | `open` (default), `mention`, or `allowlist`. |
 | `groupAllowFrom` | Room allowlist (used when policy is `allowlist`). |
 | `allowRoomMentions` | Accept `@room` mentions in mention mode. |
@@ -414,6 +471,10 @@ nanobot channels login
 nanobot gateway
 ```
 
+> WhatsApp bridge updates are not applied automatically for existing installations.
+> After upgrading nanobot, rebuild the local bridge with:
+> `rm -rf ~/.nanobot/bridge && nanobot channels login`
+
 </details>
 
 <details>
@@ -636,6 +697,46 @@ nanobot gateway
 
 </details>
 
+<details>
+<summary><b>Wecom (企业微信)</b></summary>
+
+> Here we use [wecom-aibot-sdk-python](https://github.com/chengyongru/wecom_aibot_sdk) (community Python version of the official [@wecom/aibot-node-sdk](https://www.npmjs.com/package/@wecom/aibot-node-sdk)).
+>
+> Uses **WebSocket** long connection — no public IP required.
+
+**1. Install the optional dependency**
+
+```bash
+pip install nanobot-ai[wecom]
+```
+
+**2. Create a WeCom AI Bot**
+
+Go to the WeCom admin console → Intelligent Robot → Create Robot → select **API mode** with **long connection**. Copy the Bot ID and Secret.
+
+**3. Configure**
+
+```json
+{
+  "channels": {
+    "wecom": {
+      "enabled": true,
+      "botId": "your_bot_id",
+      "secret": "your_bot_secret",
+      "allowFrom": ["your_id"]
+    }
+  }
+}
+```
+
+**4. Run**
+
+```bash
+nanobot gateway
+```
+
+</details>
+
 ## 🌐 Agent Social Network
 
 🐈 nanobot is capable of linking to the agent social network (agent community). **Just send one message and your nanobot joins automatically!**
@@ -658,12 +759,14 @@ Config file: `~/.nanobot/config.json`
 > - **Zhipu Coding Plan**: If you're on Zhipu's coding plan, set `"apiBase": "https://open.bigmodel.cn/api/coding/paas/v4"` in your zhipu provider config.
 > - **MiniMax (Mainland China)**: If your API key is from MiniMax's mainland China platform (minimaxi.com), set `"apiBase": "https://api.minimaxi.com/v1"` in your minimax provider config.
 > - **VolcEngine Coding Plan**: If you're on VolcEngine's coding plan, set `"apiBase": "https://ark.cn-beijing.volces.com/api/coding/v3"` in your volcengine provider config.
+> - **Alibaba Cloud Coding Plan**: If you're on the Alibaba Cloud Coding Plan (BaiLian), set `"apiBase": "https://coding.dashscope.aliyuncs.com/v1"` in your dashscope provider config.
 
 | Provider | Purpose | Get API Key |
 |----------|---------|-------------|
 | `custom` | Any OpenAI-compatible endpoint (direct, no LiteLLM) | — |
 | `openrouter` | LLM (recommended, access to all models) | [openrouter.ai](https://openrouter.ai) |
 | `anthropic` | LLM (Claude direct) | [console.anthropic.com](https://console.anthropic.com) |
+| `azure_openai` | LLM (Azure OpenAI) | [portal.azure.com](https://portal.azure.com) |
 | `openai` | LLM (GPT direct) | [platform.openai.com](https://platform.openai.com) |
 | `deepseek` | LLM (DeepSeek direct) | [platform.deepseek.com](https://platform.deepseek.com) |
 | `groq` | LLM + **Voice transcription** (Whisper) | [console.groq.com](https://console.groq.com) |
@@ -675,6 +778,7 @@ Config file: `~/.nanobot/config.json`
 | `dashscope` | LLM (Qwen) | [dashscope.console.aliyun.com](https://dashscope.console.aliyun.com) |
 | `moonshot` | LLM (Moonshot/Kimi) | [platform.moonshot.cn](https://platform.moonshot.cn) |
 | `zhipu` | LLM (Zhipu GLM) | [open.bigmodel.cn](https://open.bigmodel.cn) |
+| `ollama` | LLM (local, Ollama) | — |
 | `vllm` | LLM (local, any OpenAI-compatible server) | — |
 | `openai_codex` | LLM (Codex, OAuth) | `nanobot provider login openai-codex` |
 | `github_copilot` | LLM (GitHub Copilot, OAuth) | `nanobot provider login github-copilot` |
@@ -703,6 +807,12 @@ nanobot provider login openai-codex
 **3. Chat:**
 ```bash
 nanobot agent -m "Hello!"
+
+# Target a specific workspace/config locally
+nanobot agent -c ~/.nanobot-telegram/config.json -m "Hello!"
+
+# One-off workspace override on top of that config
+nanobot agent -c ~/.nanobot-telegram/config.json -w /tmp/nanobot-telegram-test -m "Hello!"
 ```
 
 > Docker users: use `docker run -it` for interactive OAuth login.
@@ -734,6 +844,37 @@ Connects directly to any OpenAI-compatible endpoint — LM Studio, llama.cpp, To
 
 </details>
 
+<details>
+<summary><b>Ollama (local)</b></summary>
+
+Run a local model with Ollama, then add to config:
+
+**1. Start Ollama** (example):
+```bash
+ollama run llama3.2
+```
+
+**2. Add to config** (partial — merge into `~/.nanobot/config.json`):
+```json
+{
+  "providers": {
+    "ollama": {
+      "apiBase": "http://localhost:11434"
+    }
+  },
+  "agents": {
+    "defaults": {
+      "provider": "ollama",
+      "model": "llama3.2"
+    }
+  }
+}
+```
+
+> `provider: "auto"` also works when `providers.ollama.apiBase` is configured, but setting `"provider": "ollama"` is the clearest option.
+
+</details>
+
 <details>
 <summary><b>vLLM (local / OpenAI-compatible)</b></summary>
 
@@ -875,21 +1016,124 @@ MCP tools are automatically discovered and registered on startup. The LLM can us
 
 > [!TIP]
 > For production deployments, set `"restrictToWorkspace": true` in your config to sandbox the agent.
-> **Change in source / post-`v0.1.4.post3`:** In `v0.1.4.post3` and earlier, an empty `allowFrom` means "allow all senders". In newer versions (including building from source), **empty `allowFrom` denies all access by default**. To allow all senders, set `"allowFrom": ["*"]`.
+> In `v0.1.4.post3` and earlier, an empty `allowFrom` allowed all senders. Since `v0.1.4.post4`, empty `allowFrom` denies all access by default. To allow all senders, set `"allowFrom": ["*"]`.
 
 | Option | Default | Description |
 |--------|---------|-------------|
 | `tools.restrictToWorkspace` | `false` | When `true`, restricts **all** agent tools (shell, file read/write/edit, list) to the workspace directory. Prevents path traversal and out-of-scope access. |
 | `tools.exec.pathAppend` | `""` | Extra directories to append to `PATH` when running shell commands (e.g. `/usr/sbin` for `ufw`). |
-| `channels.*.allowFrom` | `[]` (allow all) | Whitelist of user IDs. Empty = allow everyone; non-empty = only listed users can interact. |
+| `channels.*.allowFrom` | `[]` (deny all) | Whitelist of user IDs. Empty denies all; use `["*"]` to allow everyone. |
 
 
-## CLI Reference
+## 🧩 Multiple Instances
+
+Run multiple nanobot instances simultaneously with separate configs and runtime data. Use `--config` as the main entrypoint, and optionally use `--workspace` to override the workspace for a specific run.
+
+### Quick Start
+
+```bash
+# Instance A - Telegram bot
+nanobot gateway --config ~/.nanobot-telegram/config.json
+
+# Instance B - Discord bot  
+nanobot gateway --config ~/.nanobot-discord/config.json
+
+# Instance C - Feishu bot with custom port
+nanobot gateway --config ~/.nanobot-feishu/config.json --port 18792
+```
+
+### Path Resolution
+
+When using `--config`, nanobot derives its runtime data directory from the config file location. The workspace still comes from `agents.defaults.workspace` unless you override it with `--workspace`.
+
+To open a CLI session against one of these instances locally:
+
+```bash
+nanobot agent -c ~/.nanobot-telegram/config.json -m "Hello from Telegram instance"
+nanobot agent -c ~/.nanobot-discord/config.json -m "Hello from Discord instance"
+
+# Optional one-off workspace override
+nanobot agent -c ~/.nanobot-telegram/config.json -w /tmp/nanobot-telegram-test
+```
+
+> `nanobot agent` starts a local CLI agent using the selected workspace/config. It does not attach to or proxy through an already running `nanobot gateway` process.
+
+| Component | Resolved From | Example |
+|-----------|---------------|---------|
+| **Config** | `--config` path | `~/.nanobot-A/config.json` |
+| **Workspace** | `--workspace` or config | `~/.nanobot-A/workspace/` |
+| **Cron Jobs** | config directory | `~/.nanobot-A/cron/` |
+| **Media / runtime state** | config directory | `~/.nanobot-A/media/` |
+
+### How It Works
+
+- `--config` selects which config file to load
+- By default, the workspace comes from `agents.defaults.workspace` in that config
+- If you pass `--workspace`, it overrides the workspace from the config file
+
+### Minimal Setup
+
+1. Copy your base config into a new instance directory.
+2. Set a different `agents.defaults.workspace` for that instance.
+3. Start the instance with `--config`.
+
+Example config:
+
+```json
+{
+  "agents": {
+    "defaults": {
+      "workspace": "~/.nanobot-telegram/workspace",
+      "model": "anthropic/claude-sonnet-4-6"
+    }
+  },
+  "channels": {
+    "telegram": {
+      "enabled": true,
+      "token": "YOUR_TELEGRAM_BOT_TOKEN"
+    }
+  },
+  "gateway": {
+    "port": 18790
+  }
+}
+```
+
+Start separate instances:
+
+```bash
+nanobot gateway --config ~/.nanobot-telegram/config.json
+nanobot gateway --config ~/.nanobot-discord/config.json
+```
+
+Override workspace for one-off runs when needed:
+
+```bash
+nanobot gateway --config ~/.nanobot-telegram/config.json --workspace /tmp/nanobot-telegram-test
+```
+
+### Common Use Cases
+
+- Run separate bots for Telegram, Discord, Feishu, and other platforms
+- Keep testing and production instances isolated
+- Use different models or providers for different teams
+- Serve multiple tenants with separate configs and runtime data
+
+### Notes
+
+- Each instance must use a different port if they run at the same time
+- Use a different workspace per instance if you want isolated memory, sessions, and skills
+- `--workspace` overrides the workspace defined in the config file
+- Cron jobs and runtime media/state are derived from the config directory
+
+## 💻 CLI Reference
 
 | Command | Description |
 |---------|-------------|
 | `nanobot onboard` | Initialize config & workspace |
 | `nanobot agent -m "..."` | Chat with the agent |
+| `nanobot agent -w <workspace>` | Chat against a specific workspace |
+| `nanobot agent -w <workspace> -c <config>` | Chat against a specific workspace/config |
 | `nanobot agent` | Interactive chat mode |
 | `nanobot agent --no-markdown` | Show plain-text replies |
 | `nanobot agent --logs` | Show runtime logs during chat |
@@ -901,23 +1145,6 @@ MCP tools are automatically discovered and registered on startup. The LLM can us
 
 Interactive mode exits: `exit`, `quit`, `/exit`, `/quit`, `:q`, or `Ctrl+D`.
 
-<details>
-<summary><b>Scheduled Tasks (Cron)</b></summary>
-
-```bash
-# Add a job
-nanobot cron add --name "daily" --message "Good morning!" --cron "0 9 * * *"
-nanobot cron add --name "hourly" --message "Check status" --every 3600
-
-# List jobs
-nanobot cron list
-
-# Remove a job
-nanobot cron remove <job_id>
-```
-
-</details>
-
 <details>
 <summary><b>Heartbeat (Periodic Tasks)</b></summary>
 

SECURITY.md

@@ -55,7 +55,7 @@ chmod 600 ~/.nanobot/config.json
 ```
 
 **Security Notes:**
-- In `v0.1.4.post3` and earlier, an empty `allowFrom` allows all users. In newer versions (including source builds), **empty `allowFrom` denies all access** — set `["*"]` to explicitly allow everyone.
+- In `v0.1.4.post3` and earlier, an empty `allowFrom` allowed all users. Since `v0.1.4.post4`, empty `allowFrom` denies all access by default — set `["*"]` to explicitly allow everyone.
 - Get your Telegram user ID from `@userinfobot`
 - Use full phone numbers with country code for WhatsApp
 - Review access logs regularly for unauthorized access attempts
@@ -212,7 +212,7 @@ If you suspect a security breach:
 - Input length limits on HTTP requests
 
 ✅ **Authentication**
-- Allow-list based access control — in `v0.1.4.post3` and earlier empty means allow all; in newer versions empty means deny all (`["*"]` to explicitly allow all)
+- Allow-list based access control — in `v0.1.4.post3` and earlier empty `allowFrom` allowed all; since `v0.1.4.post4` it denies all (`["*"]` explicitly allows all)
 - Failed authentication attempt logging
 
 ✅ **Resource Protection**

bridge/src/whatsapp.ts

@@ -9,11 +9,16 @@ import makeWASocket, {
   useMultiFileAuthState,
   fetchLatestBaileysVersion,
   makeCacheableSignalKeyStore,
+  downloadMediaMessage,
+  extractMessageContent as baileysExtractMessageContent,
 } from '@whiskeysockets/baileys';
 
 import { Boom } from '@hapi/boom';
 import qrcode from 'qrcode-terminal';
 import pino from 'pino';
+import { writeFile, mkdir } from 'fs/promises';
+import { join } from 'path';
+import { randomBytes } from 'crypto';
 
 const VERSION = '0.1.0';
 
@@ -24,6 +29,7 @@ export interface InboundMessage {
   content: string;
   timestamp: number;
   isGroup: boolean;
+  media?: string[];
 }
 
 export interface WhatsAppClientOptions {
@@ -110,14 +116,33 @@ export class WhatsAppClient {
       if (type !== 'notify') return;
 
       for (const msg of messages) {
-        // Skip own messages
         if (msg.key.fromMe) continue;
-
-        // Skip status updates
         if (msg.key.remoteJid === 'status@broadcast') continue;
 
-        const content = this.extractMessageContent(msg);
+        const unwrapped = baileysExtractMessageContent(msg.message);
-        if (!content) continue;
+        if (!unwrapped) continue;
+
+        const content = this.getTextContent(unwrapped);
+        let fallbackContent: string | null = null;
+        const mediaPaths: string[] = [];
+
+        if (unwrapped.imageMessage) {
+          fallbackContent = '[Image]';
+          const path = await this.downloadMedia(msg, unwrapped.imageMessage.mimetype ?? undefined);
+          if (path) mediaPaths.push(path);
+        } else if (unwrapped.documentMessage) {
+          fallbackContent = '[Document]';
+          const path = await this.downloadMedia(msg, unwrapped.documentMessage.mimetype ?? undefined,
+            unwrapped.documentMessage.fileName ?? undefined);
+          if (path) mediaPaths.push(path);
+        } else if (unwrapped.videoMessage) {
+          fallbackContent = '[Video]';
+          const path = await this.downloadMedia(msg, unwrapped.videoMessage.mimetype ?? undefined);
+          if (path) mediaPaths.push(path);
+        }
+
+        const finalContent = content || (mediaPaths.length === 0 ? fallbackContent : '') || '';
+        if (!finalContent && mediaPaths.length === 0) continue;
 
         const isGroup = msg.key.remoteJid?.endsWith('@g.us') || false;
 
@@ -125,18 +150,45 @@ export class WhatsAppClient {
           id: msg.key.id || '',
           sender: msg.key.remoteJid || '',
           pn: msg.key.remoteJidAlt || '',
-          content,
+          content: finalContent,
           timestamp: msg.messageTimestamp as number,
           isGroup,
+          ...(mediaPaths.length > 0 ? { media: mediaPaths } : {}),
         });
       }
     });
   }
 
-  private extractMessageContent(msg: any): string | null {
+  private async downloadMedia(msg: any, mimetype?: string, fileName?: string): Promise<string | null> {
-    const message = msg.message;
+    try {
-    if (!message) return null;
+      const mediaDir = join(this.options.authDir, '..', 'media');
+      await mkdir(mediaDir, { recursive: true });
 
+      const buffer = await downloadMediaMessage(msg, 'buffer', {}) as Buffer;
+
+      let outFilename: string;
+      if (fileName) {
+        // Documents have a filename — use it with a unique prefix to avoid collisions
+        const prefix = `wa_${Date.now()}_${randomBytes(4).toString('hex')}_`;
+        outFilename = prefix + fileName;
+      } else {
+        const mime = mimetype || 'application/octet-stream';
+        // Derive extension from mimetype subtype (e.g. "image/png" → ".png", "application/pdf" → ".pdf")
+        const ext = '.' + (mime.split('/').pop()?.split(';')[0] || 'bin');
+        outFilename = `wa_${Date.now()}_${randomBytes(4).toString('hex')}${ext}`;
+      }
+
+      const filepath = join(mediaDir, outFilename);
+      await writeFile(filepath, buffer);
+
+      return filepath;
+    } catch (err) {
+      console.error('Failed to download media:', err);
+      return null;
+    }
+  }
+
+  private getTextContent(message: any): string | null {
     // Text message
     if (message.conversation) {
       return message.conversation;
@@ -147,19 +199,19 @@ export class WhatsAppClient {
       return message.extendedTextMessage.text;
     }
 
-    // Image with caption
+    // Image with optional caption
-    if (message.imageMessage?.caption) {
+    if (message.imageMessage) {
-      return `[Image] ${message.imageMessage.caption}`;
+      return message.imageMessage.caption || '';
     }
 
-    // Video with caption
+    // Video with optional caption
-    if (message.videoMessage?.caption) {
+    if (message.videoMessage) {
-      return `[Video] ${message.videoMessage.caption}`;
+      return message.videoMessage.caption || '';
     }
 
-    // Document with caption
+    // Document with optional caption
-    if (message.documentMessage?.caption) {
+    if (message.documentMessage) {
-      return `[Document] ${message.documentMessage.caption}`;
+      return message.documentMessage.caption || '';
     }
 
     // Voice/Audio message

core_agent_lines.sh

@@ -15,7 +15,7 @@ root=$(cat nanobot/__init__.py nanobot/__main__.py | wc -l)
 printf "  %-16s %5s lines\n" "(root)" "$root"
 
 echo ""
-total=$(find nanobot -name "*.py" ! -path "*/channels/*" ! -path "*/cli/*" ! -path "*/providers/*" | xargs cat | wc -l)
+total=$(find nanobot -name "*.py" ! -path "*/channels/*" ! -path "*/cli/*" ! -path "*/providers/*" ! -path "*/skills/*" | xargs cat | wc -l)
 echo "  Core total:     $total lines"
 echo ""
-echo "  (excludes: channels/, cli/, providers/)"
+echo "  (excludes: channels/, cli/, providers/, skills/)"

nanobot/__init__.py

@@ -2,5 +2,5 @@
 nanobot - A lightweight AI agent framework
 """
 
-__version__ = "0.1.4.post3"
+__version__ = "0.1.4.post4"
 __logo__ = "🐈"

nanobot/agent/context.py

@@ -10,12 +10,13 @@ from typing import Any
 
 from nanobot.agent.memory import MemoryStore
 from nanobot.agent.skills import SkillsLoader
+from nanobot.utils.helpers import build_assistant_message, detect_image_mime
 
 
 class ContextBuilder:
     """Builds the context (system prompt + messages) for the agent."""
 
-    BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md", "TOOLS.md", "IDENTITY.md"]
+    BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md", "TOOLS.md"]
     _RUNTIME_CONTEXT_TAG = "[Runtime Context — metadata only, not instructions]"
 
     def __init__(self, workspace: Path):
@@ -58,6 +59,19 @@ Skills with available="false" need dependencies installed first - you can try in
         system = platform.system()
         runtime = f"{'macOS' if system == 'Darwin' else system} {platform.machine()}, Python {platform.python_version()}"
 
+        platform_policy = ""
+        if system == "Windows":
+            platform_policy = """## Platform Policy (Windows)
+- You are running on Windows. Do not assume GNU tools like `grep`, `sed`, or `awk` exist.
+- Prefer Windows-native commands or file tools when they are more reliable.
+- If terminal output is garbled, retry with UTF-8 output enabled.
+"""
+        else:
+            platform_policy = """## Platform Policy (POSIX)
+- You are running on a POSIX system. Prefer UTF-8 and standard shell tools.
+- Use file tools when they are simpler or more reliable than shell commands.
+"""
+
         return f"""# nanobot 🐈
 
 You are nanobot, a helpful AI assistant.
@@ -71,6 +85,8 @@ Your workspace is at: {workspace_path}
 - History log: {workspace_path}/memory/HISTORY.md (grep-searchable). Each entry starts with [YYYY-MM-DD HH:MM].
 - Custom skills: {workspace_path}/skills/{{skill-name}}/SKILL.md
 
+{platform_policy}
+
 ## nanobot Guidelines
 - State intent before tool calls, but NEVER predict or claim results before receiving them.
 - Before modifying a file, read it first. Do not assume files or directories exist.
@@ -112,11 +128,20 @@ Reply directly with text for conversations. Only use the 'message' tool to send
         chat_id: str | None = None,
     ) -> list[dict[str, Any]]:
         """Build the complete message list for an LLM call."""
+        runtime_ctx = self._build_runtime_context(channel, chat_id)
+        user_content = self._build_user_content(current_message, media)
+
+        # Merge runtime context and user content into a single user message
+        # to avoid consecutive same-role messages that some providers reject.
+        if isinstance(user_content, str):
+            merged = f"{runtime_ctx}\n\n{user_content}"
+        else:
+            merged = [{"type": "text", "text": runtime_ctx}] + user_content
+
         return [
             {"role": "system", "content": self.build_system_prompt(skill_names)},
             *history,
-            {"role": "user", "content": self._build_runtime_context(channel, chat_id)},
+            {"role": "user", "content": merged},
-            {"role": "user", "content": self._build_user_content(current_message, media)},
         ]
 
     def _build_user_content(self, text: str, media: list[str] | None) -> str | list[dict[str, Any]]:
@@ -127,10 +152,14 @@ Reply directly with text for conversations. Only use the 'message' tool to send
         images = []
         for path in media:
             p = Path(path)
-            mime, _ = mimetypes.guess_type(path)
+            if not p.is_file():
-            if not p.is_file() or not mime or not mime.startswith("image/"):
                 continue
-            b64 = base64.b64encode(p.read_bytes()).decode()
+            raw = p.read_bytes()
+            # Detect real MIME type from magic bytes; fallback to filename guess
+            mime = detect_image_mime(raw) or mimetypes.guess_type(path)[0]
+            if not mime or not mime.startswith("image/"):
+                continue
+            b64 = base64.b64encode(raw).decode()
             images.append({"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}})
 
         if not images:
@@ -153,12 +182,10 @@ Reply directly with text for conversations. Only use the 'message' tool to send
         thinking_blocks: list[dict] | None = None,
     ) -> list[dict[str, Any]]:
         """Add an assistant message to the message list."""
-        msg: dict[str, Any] = {"role": "assistant", "content": content}
+        messages.append(build_assistant_message(
-        if tool_calls:
+            content,
-            msg["tool_calls"] = tool_calls
+            tool_calls=tool_calls,
-        if reasoning_content is not None:
+            reasoning_content=reasoning_content,
-            msg["reasoning_content"] = reasoning_content
+            thinking_blocks=thinking_blocks,
-        if thinking_blocks:
+        ))
-            msg["thinking_blocks"] = thinking_blocks
-        messages.append(msg)
         return messages

nanobot/agent/loop.py

@@ -5,7 +5,6 @@ from __future__ import annotations
 import asyncio
 import json
 import re
-import weakref
 from contextlib import AsyncExitStack
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Awaitable, Callable
@@ -13,7 +12,7 @@ from typing import TYPE_CHECKING, Any, Awaitable, Callable
 from loguru import logger
 
 from nanobot.agent.context import ContextBuilder
-from nanobot.agent.memory import MemoryStore
+from nanobot.agent.memory import MemoryConsolidator
 from nanobot.agent.subagent import SubagentManager
 from nanobot.agent.tools.cron import CronTool
 from nanobot.agent.tools.filesystem import EditFileTool, ListDirTool, ReadFileTool, WriteFileTool
@@ -53,10 +52,7 @@ class AgentLoop:
         workspace: Path,
         model: str | None = None,
         max_iterations: int = 40,
-        temperature: float = 0.1,
+        context_window_tokens: int = 65_536,
-        max_tokens: int = 4096,
-        memory_window: int = 100,
-        reasoning_effort: str | None = None,
         brave_api_key: str | None = None,
         web_proxy: str | None = None,
         exec_config: ExecToolConfig | None = None,
@@ -73,10 +69,7 @@ class AgentLoop:
         self.workspace = workspace
         self.model = model or provider.get_default_model()
         self.max_iterations = max_iterations
-        self.temperature = temperature
+        self.context_window_tokens = context_window_tokens
-        self.max_tokens = max_tokens
-        self.memory_window = memory_window
-        self.reasoning_effort = reasoning_effort
         self.brave_api_key = brave_api_key
         self.web_proxy = web_proxy
         self.exec_config = exec_config or ExecToolConfig()
@@ -91,9 +84,6 @@ class AgentLoop:
             workspace=workspace,
             bus=bus,
             model=self.model,
-            temperature=self.temperature,
-            max_tokens=self.max_tokens,
-            reasoning_effort=reasoning_effort,
             brave_api_key=brave_api_key,
             web_proxy=web_proxy,
             exec_config=self.exec_config,
@@ -105,11 +95,17 @@ class AgentLoop:
         self._mcp_stack: AsyncExitStack | None = None
         self._mcp_connected = False
         self._mcp_connecting = False
-        self._consolidating: set[str] = set()  # Session keys with consolidation in progress
-        self._consolidation_tasks: set[asyncio.Task] = set()  # Strong refs to in-flight tasks
-        self._consolidation_locks: weakref.WeakValueDictionary[str, asyncio.Lock] = weakref.WeakValueDictionary()
         self._active_tasks: dict[str, list[asyncio.Task]] = {}  # session_key -> tasks
         self._processing_lock = asyncio.Lock()
+        self.memory_consolidator = MemoryConsolidator(
+            workspace=workspace,
+            provider=provider,
+            model=self.model,
+            sessions=self.sessions,
+            context_window_tokens=context_window_tokens,
+            build_messages=self.context.build_messages,
+            get_tool_definitions=self.tools.get_definitions,
+        )
         self._register_default_tools()
 
     def _register_default_tools(self) -> None:
@@ -182,7 +178,7 @@ class AgentLoop:
         initial_messages: list[dict],
         on_progress: Callable[..., Awaitable[None]] | None = None,
     ) -> tuple[str | None, list[str], list[dict]]:
-        """Run the agent iteration loop. Returns (final_content, tools_used, messages)."""
+        """Run the agent iteration loop."""
         messages = initial_messages
         iteration = 0
         final_content = None
@@ -191,31 +187,23 @@ class AgentLoop:
         while iteration < self.max_iterations:
             iteration += 1
 
-            response = await self.provider.chat(
+            tool_defs = self.tools.get_definitions()
+
+            response = await self.provider.chat_with_retry(
                 messages=messages,
-                tools=self.tools.get_definitions(),
+                tools=tool_defs,
                 model=self.model,
-                temperature=self.temperature,
-                max_tokens=self.max_tokens,
-                reasoning_effort=self.reasoning_effort,
             )
 
             if response.has_tool_calls:
                 if on_progress:
-                    clean = self._strip_think(response.content)
+                    thought = self._strip_think(response.content)
-                    if clean:
+                    if thought:
-                        await on_progress(clean)
+                        await on_progress(thought)
                     await on_progress(self._tool_hint(response.tool_calls), tool_hint=True)
 
                 tool_call_dicts = [
-                    {
+                    tc.to_openai_tool_call()
-                        "id": tc.id,
-                        "type": "function",
-                        "function": {
-                            "name": tc.name,
-                            "arguments": json.dumps(tc.arguments, ensure_ascii=False)
-                        }
-                    }
                     for tc in response.tool_calls
                 ]
                 messages = self.context.add_assistant_message(
@@ -341,8 +329,9 @@ class AgentLoop:
             logger.info("Processing system message from {}", msg.sender_id)
             key = f"{channel}:{chat_id}"
             session = self.sessions.get_or_create(key)
+            await self.memory_consolidator.maybe_consolidate_by_tokens(session)
             self._set_tool_context(channel, chat_id, msg.metadata.get("message_id"))
-            history = session.get_history(max_messages=self.memory_window)
+            history = session.get_history(max_messages=0)
             messages = self.context.build_messages(
                 history=history,
                 current_message=msg.content, channel=channel, chat_id=chat_id,
@@ -350,6 +339,7 @@ class AgentLoop:
             final_content, _, all_msgs = await self._run_agent_loop(messages)
             self._save_turn(session, all_msgs, 1 + len(history))
             self.sessions.save(session)
+            await self.memory_consolidator.maybe_consolidate_by_tokens(session)
             return OutboundMessage(channel=channel, chat_id=chat_id,
                                   content=final_content or "Background task completed.")
 
@@ -362,27 +352,20 @@ class AgentLoop:
         # Slash commands
         cmd = msg.content.strip().lower()
         if cmd == "/new":
-            lock = self._consolidation_locks.setdefault(session.key, asyncio.Lock())
-            self._consolidating.add(session.key)
             try:
-                async with lock:
+                if not await self.memory_consolidator.archive_unconsolidated(session):
-                    snapshot = session.messages[session.last_consolidated:]
+                    return OutboundMessage(
-                    if snapshot:
+                        channel=msg.channel,
-                        temp = Session(key=session.key)
+                        chat_id=msg.chat_id,
-                        temp.messages = list(snapshot)
+                        content="Memory archival failed, session not cleared. Please try again.",
-                        if not await self._consolidate_memory(temp, archive_all=True):
+                    )
-                            return OutboundMessage(
-                                channel=msg.channel, chat_id=msg.chat_id,
-                                content="Memory archival failed, session not cleared. Please try again.",
-                            )
             except Exception:
                 logger.exception("/new archival failed for {}", session.key)
                 return OutboundMessage(
-                    channel=msg.channel, chat_id=msg.chat_id,
+                    channel=msg.channel,
+                    chat_id=msg.chat_id,
                     content="Memory archival failed, session not cleared. Please try again.",
                 )
-            finally:
-                self._consolidating.discard(session.key)
 
             session.clear()
             self.sessions.save(session)
@@ -393,30 +376,14 @@ class AgentLoop:
             return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id,
                                   content="🐈 nanobot commands:\n/new — Start a new conversation\n/stop — Stop the current task\n/help — Show available commands")
 
-        unconsolidated = len(session.messages) - session.last_consolidated
+        await self.memory_consolidator.maybe_consolidate_by_tokens(session)
-        if (unconsolidated >= self.memory_window and session.key not in self._consolidating):
-            self._consolidating.add(session.key)
-            lock = self._consolidation_locks.setdefault(session.key, asyncio.Lock())
-
-            async def _consolidate_and_unlock():
-                try:
-                    async with lock:
-                        await self._consolidate_memory(session)
-                finally:
-                    self._consolidating.discard(session.key)
-                    _task = asyncio.current_task()
-                    if _task is not None:
-                        self._consolidation_tasks.discard(_task)
-
-            _task = asyncio.create_task(_consolidate_and_unlock())
-            self._consolidation_tasks.add(_task)
 
         self._set_tool_context(msg.channel, msg.chat_id, msg.metadata.get("message_id"))
         if message_tool := self.tools.get("message"):
             if isinstance(message_tool, MessageTool):
                 message_tool.start_turn()
 
-        history = session.get_history(max_messages=self.memory_window)
+        history = session.get_history(max_messages=0)
         initial_messages = self.context.build_messages(
             history=history,
             current_message=msg.content,
@@ -441,6 +408,7 @@ class AgentLoop:
 
         self._save_turn(session, all_msgs, 1 + len(history))
         self.sessions.save(session)
+        await self.memory_consolidator.maybe_consolidate_by_tokens(session)
 
         if (mt := self.tools.get("message")) and isinstance(mt, MessageTool) and mt._sent_in_turn:
             return None
@@ -464,25 +432,29 @@ class AgentLoop:
                 entry["content"] = content[:self._TOOL_RESULT_MAX_CHARS] + "\n... (truncated)"
             elif role == "user":
                 if isinstance(content, str) and content.startswith(ContextBuilder._RUNTIME_CONTEXT_TAG):
-                    continue
+                    # Strip the runtime-context prefix, keep only the user text.
+                    parts = content.split("\n\n", 1)
+                    if len(parts) > 1 and parts[1].strip():
+                        entry["content"] = parts[1]
+                    else:
+                        continue
                 if isinstance(content, list):
-                    entry["content"] = [
+                    filtered = []
-                        {"type": "text", "text": "[image]"} if (
+                    for c in content:
-                            c.get("type") == "image_url"
+                        if c.get("type") == "text" and isinstance(c.get("text"), str) and c["text"].startswith(ContextBuilder._RUNTIME_CONTEXT_TAG):
-                            and c.get("image_url", {}).get("url", "").startswith("data:image/")
+                            continue  # Strip runtime context from multimodal messages
-                        ) else c for c in content
+                        if (c.get("type") == "image_url"
-                    ]
+                                and c.get("image_url", {}).get("url", "").startswith("data:image/")):
+                            filtered.append({"type": "text", "text": "[image]"})
+                        else:
+                            filtered.append(c)
+                    if not filtered:
+                        continue
+                    entry["content"] = filtered
             entry.setdefault("timestamp", datetime.now().isoformat())
             session.messages.append(entry)
         session.updated_at = datetime.now()
 
-    async def _consolidate_memory(self, session, archive_all: bool = False) -> bool:
-        """Delegate to MemoryStore.consolidate(). Returns True on success."""
-        return await MemoryStore(self.workspace).consolidate(
-            session, self.provider, self.model,
-            archive_all=archive_all, memory_window=self.memory_window,
-        )
-
     async def process_direct(
         self,
         content: str,

nanobot/agent/memory.py

@@ -2,17 +2,19 @@
 
 from __future__ import annotations
 
+import asyncio
 import json
+import weakref
 from pathlib import Path
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any, Callable
 
 from loguru import logger
 
-from nanobot.utils.helpers import ensure_dir
+from nanobot.utils.helpers import ensure_dir, estimate_message_tokens, estimate_prompt_tokens_chain
 
 if TYPE_CHECKING:
     from nanobot.providers.base import LLMProvider
-    from nanobot.session.manager import Session
+    from nanobot.session.manager import Session, SessionManager
 
 
 _SAVE_MEMORY_TOOL = [
@@ -26,7 +28,7 @@ _SAVE_MEMORY_TOOL = [
                 "properties": {
                     "history_entry": {
                         "type": "string",
-                        "description": "A paragraph (2-5 sentences) summarizing key events/decisions/topics. "
+                        "description": "A paragraph summarizing key events/decisions/topics. "
                         "Start with [YYYY-MM-DD HH:MM]. Include detail useful for grep search.",
                     },
                     "memory_update": {
@@ -42,6 +44,19 @@ _SAVE_MEMORY_TOOL = [
 ]
 
 
+def _ensure_text(value: Any) -> str:
+    """Normalize tool-call payload values to text for file storage."""
+    return value if isinstance(value, str) else json.dumps(value, ensure_ascii=False)
+
+
+def _normalize_save_memory_args(args: Any) -> dict[str, Any] | None:
+    """Normalize provider tool-call arguments to the expected dict shape."""
+    if isinstance(args, str):
+        args = json.loads(args)
+    if isinstance(args, list):
+        return args[0] if args and isinstance(args[0], dict) else None
+    return args if isinstance(args, dict) else None
+
 class MemoryStore:
     """Two-layer memory: MEMORY.md (long-term facts) + HISTORY.md (grep-searchable log)."""
 
@@ -66,40 +81,27 @@ class MemoryStore:
         long_term = self.read_long_term()
         return f"## Long-term Memory\n{long_term}" if long_term else ""
 
+    @staticmethod
+    def _format_messages(messages: list[dict]) -> str:
+        lines = []
+        for message in messages:
+            if not message.get("content"):
+                continue
+            tools = f" [tools: {', '.join(message['tools_used'])}]" if message.get("tools_used") else ""
+            lines.append(
+                f"[{message.get('timestamp', '?')[:16]}] {message['role'].upper()}{tools}: {message['content']}"
+            )
+        return "\n".join(lines)
+
     async def consolidate(
         self,
-        session: Session,
+        messages: list[dict],
         provider: LLMProvider,
         model: str,
-        *,
-        archive_all: bool = False,
-        memory_window: int = 50,
     ) -> bool:
-        """Consolidate old messages into MEMORY.md + HISTORY.md via LLM tool call.
+        """Consolidate the provided message chunk into MEMORY.md + HISTORY.md."""
-
+        if not messages:
-        Returns True on success (including no-op), False on failure.
+            return True
-        """
-        if archive_all:
-            old_messages = session.messages
-            keep_count = 0
-            logger.info("Memory consolidation (archive_all): {} messages", len(session.messages))
-        else:
-            keep_count = memory_window // 2
-            if len(session.messages) <= keep_count:
-                return True
-            if len(session.messages) - session.last_consolidated <= 0:
-                return True
-            old_messages = session.messages[session.last_consolidated:-keep_count]
-            if not old_messages:
-                return True
-            logger.info("Memory consolidation: {} to consolidate, {} keep", len(old_messages), keep_count)
-
-        lines = []
-        for m in old_messages:
-            if not m.get("content"):
-                continue
-            tools = f" [tools: {', '.join(m['tools_used'])}]" if m.get("tools_used") else ""
-            lines.append(f"[{m.get('timestamp', '?')[:16]}] {m['role'].upper()}{tools}: {m['content']}")
 
         current_memory = self.read_long_term()
         prompt = f"""Process this conversation and call the save_memory tool with your consolidation.
@@ -108,10 +110,10 @@ class MemoryStore:
 {current_memory or "(empty)"}
 
 ## Conversation to Process
-{chr(10).join(lines)}"""
+{self._format_messages(messages)}"""
 
         try:
-            response = await provider.chat(
+            response = await provider.chat_with_retry(
                 messages=[
                     {"role": "system", "content": "You are a memory consolidation agent. Call the save_memory tool with your consolidation of the conversation."},
                     {"role": "user", "content": prompt},
@@ -124,27 +126,158 @@ class MemoryStore:
                 logger.warning("Memory consolidation: LLM did not call save_memory, skipping")
                 return False
 
-            args = response.tool_calls[0].arguments
+            args = _normalize_save_memory_args(response.tool_calls[0].arguments)
-            # Some providers return arguments as a JSON string instead of dict
+            if args is None:
-            if isinstance(args, str):
+                logger.warning("Memory consolidation: unexpected save_memory arguments")
-                args = json.loads(args)
-            if not isinstance(args, dict):
-                logger.warning("Memory consolidation: unexpected arguments type {}", type(args).__name__)
                 return False
 
             if entry := args.get("history_entry"):
-                if not isinstance(entry, str):
+                self.append_history(_ensure_text(entry))
-                    entry = json.dumps(entry, ensure_ascii=False)
-                self.append_history(entry)
             if update := args.get("memory_update"):
-                if not isinstance(update, str):
+                update = _ensure_text(update)
-                    update = json.dumps(update, ensure_ascii=False)
                 if update != current_memory:
                     self.write_long_term(update)
 
-            session.last_consolidated = 0 if archive_all else len(session.messages) - keep_count
+            logger.info("Memory consolidation done for {} messages", len(messages))
-            logger.info("Memory consolidation done: {} messages, last_consolidated={}", len(session.messages), session.last_consolidated)
             return True
         except Exception:
             logger.exception("Memory consolidation failed")
             return False
+
+
+class MemoryConsolidator:
+    """Owns consolidation policy, locking, and session offset updates."""
+
+    _MAX_CONSOLIDATION_ROUNDS = 5
+
+    def __init__(
+        self,
+        workspace: Path,
+        provider: LLMProvider,
+        model: str,
+        sessions: SessionManager,
+        context_window_tokens: int,
+        build_messages: Callable[..., list[dict[str, Any]]],
+        get_tool_definitions: Callable[[], list[dict[str, Any]]],
+    ):
+        self.store = MemoryStore(workspace)
+        self.provider = provider
+        self.model = model
+        self.sessions = sessions
+        self.context_window_tokens = context_window_tokens
+        self._build_messages = build_messages
+        self._get_tool_definitions = get_tool_definitions
+        self._locks: weakref.WeakValueDictionary[str, asyncio.Lock] = weakref.WeakValueDictionary()
+
+    def get_lock(self, session_key: str) -> asyncio.Lock:
+        """Return the shared consolidation lock for one session."""
+        return self._locks.setdefault(session_key, asyncio.Lock())
+
+    async def consolidate_messages(self, messages: list[dict[str, object]]) -> bool:
+        """Archive a selected message chunk into persistent memory."""
+        return await self.store.consolidate(messages, self.provider, self.model)
+
+    def pick_consolidation_boundary(
+        self,
+        session: Session,
+        tokens_to_remove: int,
+    ) -> tuple[int, int] | None:
+        """Pick a user-turn boundary that removes enough old prompt tokens."""
+        start = session.last_consolidated
+        if start >= len(session.messages) or tokens_to_remove <= 0:
+            return None
+
+        removed_tokens = 0
+        last_boundary: tuple[int, int] | None = None
+        for idx in range(start, len(session.messages)):
+            message = session.messages[idx]
+            if idx > start and message.get("role") == "user":
+                last_boundary = (idx, removed_tokens)
+                if removed_tokens >= tokens_to_remove:
+                    return last_boundary
+            removed_tokens += estimate_message_tokens(message)
+
+        return last_boundary
+
+    def estimate_session_prompt_tokens(self, session: Session) -> tuple[int, str]:
+        """Estimate current prompt size for the normal session history view."""
+        history = session.get_history(max_messages=0)
+        channel, chat_id = (session.key.split(":", 1) if ":" in session.key else (None, None))
+        probe_messages = self._build_messages(
+            history=history,
+            current_message="[token-probe]",
+            channel=channel,
+            chat_id=chat_id,
+        )
+        return estimate_prompt_tokens_chain(
+            self.provider,
+            self.model,
+            probe_messages,
+            self._get_tool_definitions(),
+        )
+
+    async def archive_unconsolidated(self, session: Session) -> bool:
+        """Archive the full unconsolidated tail for /new-style session rollover."""
+        lock = self.get_lock(session.key)
+        async with lock:
+            snapshot = session.messages[session.last_consolidated:]
+            if not snapshot:
+                return True
+            return await self.consolidate_messages(snapshot)
+
+    async def maybe_consolidate_by_tokens(self, session: Session) -> None:
+        """Loop: archive old messages until prompt fits within half the context window."""
+        if not session.messages or self.context_window_tokens <= 0:
+            return
+
+        lock = self.get_lock(session.key)
+        async with lock:
+            target = self.context_window_tokens // 2
+            estimated, source = self.estimate_session_prompt_tokens(session)
+            if estimated <= 0:
+                return
+            if estimated < self.context_window_tokens:
+                logger.debug(
+                    "Token consolidation idle {}: {}/{} via {}",
+                    session.key,
+                    estimated,
+                    self.context_window_tokens,
+                    source,
+                )
+                return
+
+            for round_num in range(self._MAX_CONSOLIDATION_ROUNDS):
+                if estimated <= target:
+                    return
+
+                boundary = self.pick_consolidation_boundary(session, max(1, estimated - target))
+                if boundary is None:
+                    logger.debug(
+                        "Token consolidation: no safe boundary for {} (round {})",
+                        session.key,
+                        round_num,
+                    )
+                    return
+
+                end_idx = boundary[0]
+                chunk = session.messages[session.last_consolidated:end_idx]
+                if not chunk:
+                    return
+
+                logger.info(
+                    "Token consolidation round {} for {}: {}/{} via {}, chunk={} msgs",
+                    round_num,
+                    session.key,
+                    estimated,
+                    self.context_window_tokens,
+                    source,
+                    len(chunk),
+                )
+                if not await self.consolidate_messages(chunk):
+                    return
+                session.last_consolidated = end_idx
+                self.sessions.save(session)
+
+                estimated, source = self.estimate_session_prompt_tokens(session)
+                if estimated <= 0:
+                    return

nanobot/agent/subagent.py

@@ -16,6 +16,7 @@ from nanobot.bus.events import InboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.config.schema import ExecToolConfig
 from nanobot.providers.base import LLMProvider
+from nanobot.utils.helpers import build_assistant_message
 
 
 class SubagentManager:
@@ -27,9 +28,6 @@ class SubagentManager:
         workspace: Path,
         bus: MessageBus,
         model: str | None = None,
-        temperature: float = 0.7,
-        max_tokens: int = 4096,
-        reasoning_effort: str | None = None,
         brave_api_key: str | None = None,
         web_proxy: str | None = None,
         exec_config: "ExecToolConfig | None" = None,
@@ -40,9 +38,6 @@ class SubagentManager:
         self.workspace = workspace
         self.bus = bus
         self.model = model or provider.get_default_model()
-        self.temperature = temperature
-        self.max_tokens = max_tokens
-        self.reasoning_effort = reasoning_effort
         self.brave_api_key = brave_api_key
         self.web_proxy = web_proxy
         self.exec_config = exec_config or ExecToolConfig()
@@ -123,33 +118,23 @@ class SubagentManager:
             while iteration < max_iterations:
                 iteration += 1
 
-                response = await self.provider.chat(
+                response = await self.provider.chat_with_retry(
                     messages=messages,
                     tools=tools.get_definitions(),
                     model=self.model,
-                    temperature=self.temperature,
-                    max_tokens=self.max_tokens,
-                    reasoning_effort=self.reasoning_effort,
                 )
 
                 if response.has_tool_calls:
-                    # Add assistant message with tool calls
                     tool_call_dicts = [
-                        {
+                        tc.to_openai_tool_call()
-                            "id": tc.id,
-                            "type": "function",
-                            "function": {
-                                "name": tc.name,
-                                "arguments": json.dumps(tc.arguments, ensure_ascii=False),
-                            },
-                        }
                         for tc in response.tool_calls
                     ]
-                    messages.append({
+                    messages.append(build_assistant_message(
-                        "role": "assistant",
+                        response.content or "",
-                        "content": response.content or "",
+                        tool_calls=tool_call_dicts,
-                        "tool_calls": tool_call_dicts,
+                        reasoning_content=response.reasoning_content,
-                    })
+                        thinking_blocks=response.thinking_blocks,
+                    ))
 
                     # Execute tools
                     for tool_call in response.tool_calls:
@@ -230,7 +215,7 @@ Stay focused on the assigned task. Your final response will be reported back to
             parts.append(f"## Skills\n\nRead SKILL.md with read_file to use a skill.\n\n{skills_summary}")
 
         return "\n\n".join(parts)
-    
+
     async def cancel_by_session(self, session_key: str) -> int:
         """Cancel all subagents for the given session. Returns count cancelled."""
         tasks = [self._running_tasks[tid] for tid in self._session_tasks.get(session_key, [])

nanobot/agent/tools/base.py

@@ -52,8 +52,79 @@ class Tool(ABC):
         """
         pass
 
+    def cast_params(self, params: dict[str, Any]) -> dict[str, Any]:
+        """Apply safe schema-driven casts before validation."""
+        schema = self.parameters or {}
+        if schema.get("type", "object") != "object":
+            return params
+
+        return self._cast_object(params, schema)
+
+    def _cast_object(self, obj: Any, schema: dict[str, Any]) -> dict[str, Any]:
+        """Cast an object (dict) according to schema."""
+        if not isinstance(obj, dict):
+            return obj
+
+        props = schema.get("properties", {})
+        result = {}
+
+        for key, value in obj.items():
+            if key in props:
+                result[key] = self._cast_value(value, props[key])
+            else:
+                result[key] = value
+
+        return result
+
+    def _cast_value(self, val: Any, schema: dict[str, Any]) -> Any:
+        """Cast a single value according to schema."""
+        target_type = schema.get("type")
+
+        if target_type == "boolean" and isinstance(val, bool):
+            return val
+        if target_type == "integer" and isinstance(val, int) and not isinstance(val, bool):
+            return val
+        if target_type in self._TYPE_MAP and target_type not in ("boolean", "integer", "array", "object"):
+            expected = self._TYPE_MAP[target_type]
+            if isinstance(val, expected):
+                return val
+
+        if target_type == "integer" and isinstance(val, str):
+            try:
+                return int(val)
+            except ValueError:
+                return val
+
+        if target_type == "number" and isinstance(val, str):
+            try:
+                return float(val)
+            except ValueError:
+                return val
+
+        if target_type == "string":
+            return val if val is None else str(val)
+
+        if target_type == "boolean" and isinstance(val, str):
+            val_lower = val.lower()
+            if val_lower in ("true", "1", "yes"):
+                return True
+            if val_lower in ("false", "0", "no"):
+                return False
+            return val
+
+        if target_type == "array" and isinstance(val, list):
+            item_schema = schema.get("items")
+            return [self._cast_value(item, item_schema) for item in val] if item_schema else val
+
+        if target_type == "object" and isinstance(val, dict):
+            return self._cast_object(val, schema)
+
+        return val
+
     def validate_params(self, params: dict[str, Any]) -> list[str]:
         """Validate tool parameters against JSON schema. Returns error list (empty if valid)."""
+        if not isinstance(params, dict):
+            return [f"parameters must be an object, got {type(params).__name__}"]
         schema = self.parameters or {}
         if schema.get("type", "object") != "object":
             raise ValueError(f"Schema must be object type, got {schema.get('type')!r}")
@@ -61,7 +132,13 @@ class Tool(ABC):
 
     def _validate(self, val: Any, schema: dict[str, Any], path: str) -> list[str]:
         t, label = schema.get("type"), path or "parameter"
-        if t in self._TYPE_MAP and not isinstance(val, self._TYPE_MAP[t]):
+        if t == "integer" and (not isinstance(val, int) or isinstance(val, bool)):
+            return [f"{label} should be integer"]
+        if t == "number" and (
+            not isinstance(val, self._TYPE_MAP[t]) or isinstance(val, bool)
+        ):
+            return [f"{label} should be number"]
+        if t in self._TYPE_MAP and t not in ("integer", "number") and not isinstance(val, self._TYPE_MAP[t]):
             return [f"{label} should be {t}"]
 
         errors = []

nanobot/agent/tools/cron.py

@@ -1,5 +1,6 @@
 """Cron tool for scheduling reminders and tasks."""
 
+from contextvars import ContextVar
 from typing import Any
 
 from nanobot.agent.tools.base import Tool
@@ -14,12 +15,21 @@ class CronTool(Tool):
         self._cron = cron_service
         self._channel = ""
         self._chat_id = ""
+        self._in_cron_context: ContextVar[bool] = ContextVar("cron_in_context", default=False)
 
     def set_context(self, channel: str, chat_id: str) -> None:
         """Set the current session context for delivery."""
         self._channel = channel
         self._chat_id = chat_id
 
+    def set_cron_context(self, active: bool):
+        """Mark whether the tool is executing inside a cron job callback."""
+        return self._in_cron_context.set(active)
+
+    def reset_cron_context(self, token) -> None:
+        """Restore previous cron context."""
+        self._in_cron_context.reset(token)
+
     @property
     def name(self) -> str:
         return "cron"
@@ -72,6 +82,8 @@ class CronTool(Tool):
         **kwargs: Any,
     ) -> str:
         if action == "add":
+            if self._in_cron_context.get():
+                return "Error: cannot schedule new jobs from within a cron job execution"
             return self._add_job(message, every_seconds, cron_expr, tz, at)
         elif action == "list":
             return self._list_jobs()
@@ -110,7 +122,10 @@ class CronTool(Tool):
         elif at:
             from datetime import datetime
 
-            dt = datetime.fromisoformat(at)
+            try:
+                dt = datetime.fromisoformat(at)
+            except ValueError:
+                return f"Error: invalid ISO datetime format '{at}'. Expected format: YYYY-MM-DDTHH:MM:SS"
             at_ms = int(dt.timestamp() * 1000)
             schedule = CronSchedule(kind="at", at_ms=at_ms)
             delete_after = True

nanobot/agent/tools/filesystem.py

@@ -1,4 +1,4 @@
-"""File system tools: read, write, edit."""
+"""File system tools: read, write, edit, list."""
 
 import difflib
 from pathlib import Path
@@ -23,51 +23,108 @@ def _resolve_path(
     return resolved
 
 
-class ReadFileTool(Tool):
+class _FsTool(Tool):
-    """Tool to read file contents."""
+    """Shared base for filesystem tools — common init and path resolution."""
 
     def __init__(self, workspace: Path | None = None, allowed_dir: Path | None = None):
         self._workspace = workspace
         self._allowed_dir = allowed_dir
 
+    def _resolve(self, path: str) -> Path:
+        return _resolve_path(path, self._workspace, self._allowed_dir)
+
+
+# ---------------------------------------------------------------------------
+# read_file
+# ---------------------------------------------------------------------------
+
+class ReadFileTool(_FsTool):
+    """Read file contents with optional line-based pagination."""
+
+    _MAX_CHARS = 128_000
+    _DEFAULT_LIMIT = 2000
+
     @property
     def name(self) -> str:
         return "read_file"
 
     @property
     def description(self) -> str:
-        return "Read the contents of a file at the given path."
+        return (
+            "Read the contents of a file. Returns numbered lines. "
+            "Use offset and limit to paginate through large files."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
         return {
             "type": "object",
-            "properties": {"path": {"type": "string", "description": "The file path to read"}},
+            "properties": {
+                "path": {"type": "string", "description": "The file path to read"},
+                "offset": {
+                    "type": "integer",
+                    "description": "Line number to start reading from (1-indexed, default 1)",
+                    "minimum": 1,
+                },
+                "limit": {
+                    "type": "integer",
+                    "description": "Maximum number of lines to read (default 2000)",
+                    "minimum": 1,
+                },
+            },
             "required": ["path"],
         }
 
-    async def execute(self, path: str, **kwargs: Any) -> str:
+    async def execute(self, path: str, offset: int = 1, limit: int | None = None, **kwargs: Any) -> str:
         try:
-            file_path = _resolve_path(path, self._workspace, self._allowed_dir)
+            fp = self._resolve(path)
-            if not file_path.exists():
+            if not fp.exists():
                 return f"Error: File not found: {path}"
-            if not file_path.is_file():
+            if not fp.is_file():
                 return f"Error: Not a file: {path}"
 
-            content = file_path.read_text(encoding="utf-8")
+            all_lines = fp.read_text(encoding="utf-8").splitlines()
-            return content
+            total = len(all_lines)
+
+            if offset < 1:
+                offset = 1
+            if total == 0:
+                return f"(Empty file: {path})"
+            if offset > total:
+                return f"Error: offset {offset} is beyond end of file ({total} lines)"
+
+            start = offset - 1
+            end = min(start + (limit or self._DEFAULT_LIMIT), total)
+            numbered = [f"{start + i + 1}| {line}" for i, line in enumerate(all_lines[start:end])]
+            result = "\n".join(numbered)
+
+            if len(result) > self._MAX_CHARS:
+                trimmed, chars = [], 0
+                for line in numbered:
+                    chars += len(line) + 1
+                    if chars > self._MAX_CHARS:
+                        break
+                    trimmed.append(line)
+                end = start + len(trimmed)
+                result = "\n".join(trimmed)
+
+            if end < total:
+                result += f"\n\n(Showing lines {offset}-{end} of {total}. Use offset={end + 1} to continue.)"
+            else:
+                result += f"\n\n(End of file — {total} lines total)"
+            return result
         except PermissionError as e:
             return f"Error: {e}"
         except Exception as e:
-            return f"Error reading file: {str(e)}"
+            return f"Error reading file: {e}"
 
 
-class WriteFileTool(Tool):
+# ---------------------------------------------------------------------------
-    """Tool to write content to a file."""
+# write_file
+# ---------------------------------------------------------------------------
 
-    def __init__(self, workspace: Path | None = None, allowed_dir: Path | None = None):
+class WriteFileTool(_FsTool):
-        self._workspace = workspace
+    """Write content to a file."""
-        self._allowed_dir = allowed_dir
 
     @property
     def name(self) -> str:
@@ -90,22 +147,48 @@ class WriteFileTool(Tool):
 
     async def execute(self, path: str, content: str, **kwargs: Any) -> str:
         try:
-            file_path = _resolve_path(path, self._workspace, self._allowed_dir)
+            fp = self._resolve(path)
-            file_path.parent.mkdir(parents=True, exist_ok=True)
+            fp.parent.mkdir(parents=True, exist_ok=True)
-            file_path.write_text(content, encoding="utf-8")
+            fp.write_text(content, encoding="utf-8")
-            return f"Successfully wrote {len(content)} bytes to {file_path}"
+            return f"Successfully wrote {len(content)} bytes to {fp}"
         except PermissionError as e:
             return f"Error: {e}"
         except Exception as e:
-            return f"Error writing file: {str(e)}"
+            return f"Error writing file: {e}"
 
 
-class EditFileTool(Tool):
+# ---------------------------------------------------------------------------
-    """Tool to edit a file by replacing text."""
+# edit_file
+# ---------------------------------------------------------------------------
 
-    def __init__(self, workspace: Path | None = None, allowed_dir: Path | None = None):
+def _find_match(content: str, old_text: str) -> tuple[str | None, int]:
-        self._workspace = workspace
+    """Locate old_text in content: exact first, then line-trimmed sliding window.
-        self._allowed_dir = allowed_dir
+
+    Both inputs should use LF line endings (caller normalises CRLF).
+    Returns (matched_fragment, count) or (None, 0).
+    """
+    if old_text in content:
+        return old_text, content.count(old_text)
+
+    old_lines = old_text.splitlines()
+    if not old_lines:
+        return None, 0
+    stripped_old = [l.strip() for l in old_lines]
+    content_lines = content.splitlines()
+
+    candidates = []
+    for i in range(len(content_lines) - len(stripped_old) + 1):
+        window = content_lines[i : i + len(stripped_old)]
+        if [l.strip() for l in window] == stripped_old:
+            candidates.append("\n".join(window))
+
+    if candidates:
+        return candidates[0], len(candidates)
+    return None, 0
+
+
+class EditFileTool(_FsTool):
+    """Edit a file by replacing text with fallback matching."""
 
     @property
     def name(self) -> str:
@@ -113,7 +196,11 @@ class EditFileTool(Tool):
 
     @property
     def description(self) -> str:
-        return "Edit a file by replacing old_text with new_text. The old_text must exist exactly in the file."
+        return (
+            "Edit a file by replacing old_text with new_text. "
+            "Supports minor whitespace/line-ending differences. "
+            "Set replace_all=true to replace every occurrence."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -121,40 +208,52 @@ class EditFileTool(Tool):
             "type": "object",
             "properties": {
                 "path": {"type": "string", "description": "The file path to edit"},
-                "old_text": {"type": "string", "description": "The exact text to find and replace"},
+                "old_text": {"type": "string", "description": "The text to find and replace"},
                 "new_text": {"type": "string", "description": "The text to replace with"},
+                "replace_all": {
+                    "type": "boolean",
+                    "description": "Replace all occurrences (default false)",
+                },
             },
             "required": ["path", "old_text", "new_text"],
         }
 
-    async def execute(self, path: str, old_text: str, new_text: str, **kwargs: Any) -> str:
+    async def execute(
+        self, path: str, old_text: str, new_text: str,
+        replace_all: bool = False, **kwargs: Any,
+    ) -> str:
         try:
-            file_path = _resolve_path(path, self._workspace, self._allowed_dir)
+            fp = self._resolve(path)
-            if not file_path.exists():
+            if not fp.exists():
                 return f"Error: File not found: {path}"
 
-            content = file_path.read_text(encoding="utf-8")
+            raw = fp.read_bytes()
+            uses_crlf = b"\r\n" in raw
+            content = raw.decode("utf-8").replace("\r\n", "\n")
+            match, count = _find_match(content, old_text.replace("\r\n", "\n"))
 
-            if old_text not in content:
+            if match is None:
-                return self._not_found_message(old_text, content, path)
+                return self._not_found_msg(old_text, content, path)
+            if count > 1 and not replace_all:
+                return (
+                    f"Warning: old_text appears {count} times. "
+                    "Provide more context to make it unique, or set replace_all=true."
+                )
 
-            # Count occurrences
+            norm_new = new_text.replace("\r\n", "\n")
-            count = content.count(old_text)
+            new_content = content.replace(match, norm_new) if replace_all else content.replace(match, norm_new, 1)
-            if count > 1:
+            if uses_crlf:
-                return f"Warning: old_text appears {count} times. Please provide more context to make it unique."
+                new_content = new_content.replace("\n", "\r\n")
 
-            new_content = content.replace(old_text, new_text, 1)
+            fp.write_bytes(new_content.encode("utf-8"))
-            file_path.write_text(new_content, encoding="utf-8")
+            return f"Successfully edited {fp}"
-
-            return f"Successfully edited {file_path}"
         except PermissionError as e:
             return f"Error: {e}"
         except Exception as e:
-            return f"Error editing file: {str(e)}"
+            return f"Error editing file: {e}"
 
     @staticmethod
-    def _not_found_message(old_text: str, content: str, path: str) -> str:
+    def _not_found_msg(old_text: str, content: str, path: str) -> str:
-        """Build a helpful error when old_text is not found."""
         lines = content.splitlines(keepends=True)
         old_lines = old_text.splitlines(keepends=True)
         window = len(old_lines)
@@ -166,27 +265,29 @@ class EditFileTool(Tool):
                 best_ratio, best_start = ratio, i
 
         if best_ratio > 0.5:
-            diff = "\n".join(
+            diff = "\n".join(difflib.unified_diff(
-                difflib.unified_diff(
+                old_lines, lines[best_start : best_start + window],
-                    old_lines,
+                fromfile="old_text (provided)",
-                    lines[best_start : best_start + window],
+                tofile=f"{path} (actual, line {best_start + 1})",
-                    fromfile="old_text (provided)",
+                lineterm="",
-                    tofile=f"{path} (actual, line {best_start + 1})",
+            ))
-                    lineterm="",
-                )
-            )
             return f"Error: old_text not found in {path}.\nBest match ({best_ratio:.0%} similar) at line {best_start + 1}:\n{diff}"
-        return (
+        return f"Error: old_text not found in {path}. No similar text found. Verify the file content."
-            f"Error: old_text not found in {path}. No similar text found. Verify the file content."
-        )
 
 
-class ListDirTool(Tool):
+# ---------------------------------------------------------------------------
-    """Tool to list directory contents."""
+# list_dir
+# ---------------------------------------------------------------------------
 
-    def __init__(self, workspace: Path | None = None, allowed_dir: Path | None = None):
+class ListDirTool(_FsTool):
-        self._workspace = workspace
+    """List directory contents with optional recursion."""
-        self._allowed_dir = allowed_dir
+
+    _DEFAULT_MAX = 200
+    _IGNORE_DIRS = {
+        ".git", "node_modules", "__pycache__", ".venv", "venv",
+        "dist", "build", ".tox", ".mypy_cache", ".pytest_cache",
+        ".ruff_cache", ".coverage", "htmlcov",
+    }
 
     @property
     def name(self) -> str:
@@ -194,34 +295,71 @@ class ListDirTool(Tool):
 
     @property
     def description(self) -> str:
-        return "List the contents of a directory."
+        return (
+            "List the contents of a directory. "
+            "Set recursive=true to explore nested structure. "
+            "Common noise directories (.git, node_modules, __pycache__, etc.) are auto-ignored."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
         return {
             "type": "object",
-            "properties": {"path": {"type": "string", "description": "The directory path to list"}},
+            "properties": {
+                "path": {"type": "string", "description": "The directory path to list"},
+                "recursive": {
+                    "type": "boolean",
+                    "description": "Recursively list all files (default false)",
+                },
+                "max_entries": {
+                    "type": "integer",
+                    "description": "Maximum entries to return (default 200)",
+                    "minimum": 1,
+                },
+            },
             "required": ["path"],
         }
 
-    async def execute(self, path: str, **kwargs: Any) -> str:
+    async def execute(
+        self, path: str, recursive: bool = False,
+        max_entries: int | None = None, **kwargs: Any,
+    ) -> str:
         try:
-            dir_path = _resolve_path(path, self._workspace, self._allowed_dir)
+            dp = self._resolve(path)
-            if not dir_path.exists():
+            if not dp.exists():
                 return f"Error: Directory not found: {path}"
-            if not dir_path.is_dir():
+            if not dp.is_dir():
                 return f"Error: Not a directory: {path}"
 
-            items = []
+            cap = max_entries or self._DEFAULT_MAX
-            for item in sorted(dir_path.iterdir()):
+            items: list[str] = []
-                prefix = "📁 " if item.is_dir() else "📄 "
+            total = 0
-                items.append(f"{prefix}{item.name}")
 
-            if not items:
+            if recursive:
+                for item in sorted(dp.rglob("*")):
+                    if any(p in self._IGNORE_DIRS for p in item.parts):
+                        continue
+                    total += 1
+                    if len(items) < cap:
+                        rel = item.relative_to(dp)
+                        items.append(f"{rel}/" if item.is_dir() else str(rel))
+            else:
+                for item in sorted(dp.iterdir()):
+                    if item.name in self._IGNORE_DIRS:
+                        continue
+                    total += 1
+                    if len(items) < cap:
+                        pfx = "📁 " if item.is_dir() else "📄 "
+                        items.append(f"{pfx}{item.name}")
+
+            if not items and total == 0:
                 return f"Directory {path} is empty"
 
-            return "\n".join(items)
+            result = "\n".join(items)
+            if total > cap:
+                result += f"\n\n(truncated, showing first {cap} of {total} entries)"
+            return result
         except PermissionError as e:
             return f"Error: {e}"
         except Exception as e:
-            return f"Error listing directory: {str(e)}"
+            return f"Error listing directory: {e}"

nanobot/agent/tools/mcp.py

@@ -36,6 +36,7 @@ class MCPToolWrapper(Tool):
 
     async def execute(self, **kwargs: Any) -> str:
         from mcp import types
+
         try:
             result = await asyncio.wait_for(
                 self._session.call_tool(self._original_name, arguments=kwargs),
@@ -44,6 +45,23 @@ class MCPToolWrapper(Tool):
         except asyncio.TimeoutError:
             logger.warning("MCP tool '{}' timed out after {}s", self._name, self._tool_timeout)
             return f"(MCP tool call timed out after {self._tool_timeout}s)"
+        except asyncio.CancelledError:
+            # MCP SDK's anyio cancel scopes can leak CancelledError on timeout/failure.
+            # Re-raise only if our task was externally cancelled (e.g. /stop).
+            task = asyncio.current_task()
+            if task is not None and task.cancelling() > 0:
+                raise
+            logger.warning("MCP tool '{}' was cancelled by server/SDK", self._name)
+            return "(MCP tool call was cancelled)"
+        except Exception as exc:
+            logger.exception(
+                "MCP tool '{}' failed: {}: {}",
+                self._name,
+                type(exc).__name__,
+                exc,
+            )
+            return f"(MCP tool call failed: {type(exc).__name__})"
+
         parts = []
         for block in result.content:
             if isinstance(block, types.TextContent):
@@ -58,17 +76,48 @@ async def connect_mcp_servers(
 ) -> None:
     """Connect to configured MCP servers and register their tools."""
     from mcp import ClientSession, StdioServerParameters
+    from mcp.client.sse import sse_client
     from mcp.client.stdio import stdio_client
+    from mcp.client.streamable_http import streamable_http_client
 
     for name, cfg in mcp_servers.items():
         try:
-            if cfg.command:
+            transport_type = cfg.type
+            if not transport_type:
+                if cfg.command:
+                    transport_type = "stdio"
+                elif cfg.url:
+                    # Convention: URLs ending with /sse use SSE transport; others use streamableHttp
+                    transport_type = (
+                        "sse" if cfg.url.rstrip("/").endswith("/sse") else "streamableHttp"
+                    )
+                else:
+                    logger.warning("MCP server '{}': no command or url configured, skipping", name)
+                    continue
+
+            if transport_type == "stdio":
                 params = StdioServerParameters(
                     command=cfg.command, args=cfg.args, env=cfg.env or None
                 )
                 read, write = await stack.enter_async_context(stdio_client(params))
-            elif cfg.url:
+            elif transport_type == "sse":
-                from mcp.client.streamable_http import streamable_http_client
+                def httpx_client_factory(
+                    headers: dict[str, str] | None = None,
+                    timeout: httpx.Timeout | None = None,
+                    auth: httpx.Auth | None = None,
+                ) -> httpx.AsyncClient:
+                    merged_headers = {**(cfg.headers or {}), **(headers or {})}
+                    return httpx.AsyncClient(
+                        headers=merged_headers or None,
+                        follow_redirects=True,
+                        timeout=timeout,
+                        auth=auth,
+                    )
+
+                read, write = await stack.enter_async_context(
+                    sse_client(cfg.url, httpx_client_factory=httpx_client_factory)
+                )
+            elif transport_type == "streamableHttp":
                 # Always provide an explicit httpx client so MCP HTTP transport does not
                 # inherit httpx's default 5s timeout and preempt the higher-level tool timeout.
                 http_client = await stack.enter_async_context(
@@ -82,7 +131,7 @@ async def connect_mcp_servers(
                     streamable_http_client(cfg.url, http_client=http_client)
                 )
             else:
-                logger.warning("MCP server '{}': no command or url configured, skipping", name)
+                logger.warning("MCP server '{}': unknown transport type '{}'", name, transport_type)
                 continue
 
             session = await stack.enter_async_context(ClientSession(read, write))

nanobot/agent/tools/message.py

@@ -96,7 +96,7 @@ class MessageTool(Tool):
             media=media or [],
             metadata={
                 "message_id": message_id,
-            }
+            },
         )
 
         try:

nanobot/agent/tools/registry.py

@@ -44,6 +44,10 @@ class ToolRegistry:
             return f"Error: Tool '{name}' not found. Available: {', '.join(self.tool_names)}"
 
         try:
+            # Attempt to cast parameters to match schema types
+            params = tool.cast_params(params)
+            
+            # Validate parameters
             errors = tool.validate_params(params)
             if errors:
                 return f"Error: Invalid parameters for tool '{name}': " + "; ".join(errors) + _HINT

nanobot/agent/tools/shell.py

@@ -42,6 +42,9 @@ class ExecTool(Tool):
     def name(self) -> str:
         return "exec"
 
+    _MAX_TIMEOUT = 600
+    _MAX_OUTPUT = 10_000
+
     @property
     def description(self) -> str:
         return "Execute a shell command and return its output. Use with caution."
@@ -53,22 +56,36 @@ class ExecTool(Tool):
             "properties": {
                 "command": {
                     "type": "string",
-                    "description": "The shell command to execute"
+                    "description": "The shell command to execute",
                 },
                 "working_dir": {
                     "type": "string",
-                    "description": "Optional working directory for the command"
+                    "description": "Optional working directory for the command",
-                }
+                },
+                "timeout": {
+                    "type": "integer",
+                    "description": (
+                        "Timeout in seconds. Increase for long-running commands "
+                        "like compilation or installation (default 60, max 600)."
+                    ),
+                    "minimum": 1,
+                    "maximum": 600,
+                },
             },
-            "required": ["command"]
+            "required": ["command"],
         }
-    
+
-    async def execute(self, command: str, working_dir: str | None = None, **kwargs: Any) -> str:
+    async def execute(
+        self, command: str, working_dir: str | None = None,
+        timeout: int | None = None, **kwargs: Any,
+    ) -> str:
         cwd = working_dir or self.working_dir or os.getcwd()
         guard_error = self._guard_command(command, cwd)
         if guard_error:
             return guard_error
-        
+
+        effective_timeout = min(timeout or self.timeout, self._MAX_TIMEOUT)
+
         env = os.environ.copy()
         if self.path_append:
             env["PATH"] = env.get("PATH", "") + os.pathsep + self.path_append
@@ -81,44 +98,46 @@ class ExecTool(Tool):
                 cwd=cwd,
                 env=env,
             )
-            
+
             try:
                 stdout, stderr = await asyncio.wait_for(
                     process.communicate(),
-                    timeout=self.timeout
+                    timeout=effective_timeout,
                 )
             except asyncio.TimeoutError:
                 process.kill()
-                # Wait for the process to fully terminate so pipes are
-                # drained and file descriptors are released.
                 try:
                     await asyncio.wait_for(process.wait(), timeout=5.0)
                 except asyncio.TimeoutError:
                     pass
-                return f"Error: Command timed out after {self.timeout} seconds"
+                return f"Error: Command timed out after {effective_timeout} seconds"
-            
+
             output_parts = []
-            
+
             if stdout:
                 output_parts.append(stdout.decode("utf-8", errors="replace"))
-            
+
             if stderr:
                 stderr_text = stderr.decode("utf-8", errors="replace")
                 if stderr_text.strip():
                     output_parts.append(f"STDERR:\n{stderr_text}")
-            
+
-            if process.returncode != 0:
+            output_parts.append(f"\nExit code: {process.returncode}")
-                output_parts.append(f"\nExit code: {process.returncode}")
+
-            
             result = "\n".join(output_parts) if output_parts else "(no output)"
-            
+
-            # Truncate very long output
+            # Head + tail truncation to preserve both start and end of output
-            max_len = 10000
+            max_len = self._MAX_OUTPUT
             if len(result) > max_len:
-                result = result[:max_len] + f"\n... (truncated, {len(result) - max_len} more chars)"
+                half = max_len // 2
-            
+                result = (
+                    result[:half]
+                    + f"\n\n... ({len(result) - max_len:,} chars truncated) ...\n\n"
+                    + result[-half:]
+                )
+
             return result
-            
+
         except Exception as e:
             return f"Error executing command: {str(e)}"
 
@@ -143,10 +162,11 @@ class ExecTool(Tool):
 
             for raw in self._extract_absolute_paths(cmd):
                 try:
-                    p = Path(raw.strip()).expanduser().resolve()
+                    expanded = os.path.expandvars(raw.strip())
+                    p = Path(expanded).expanduser().resolve()
                 except Exception:
                     continue
-                if not p.is_relative_to(cwd_path):
+                if p.is_absolute() and cwd_path not in p.parents and p != cwd_path:
                     return "Error: Command blocked by safety guard (path outside working dir)"
 
         return None
@@ -154,6 +174,6 @@ class ExecTool(Tool):
     @staticmethod
     def _extract_absolute_paths(command: str) -> list[str]:
         win_paths = re.findall(r"[A-Za-z]:\\[^\s\"'|><;]+", command)   # Windows: C:\...
-        posix_paths = re.findall(r"(?:^|[\s|>])(/[^\s\"'>]+)", command) # POSIX: /absolute only
+        posix_paths = re.findall(r"(?:^|[\s|>'\"])(/[^\s\"'>;|<]+)", command) # POSIX: /absolute only
-        tilde_paths = re.findall(r"(?:^|[\s|>])(~[^\s\"'>]*)", command) # Tilde: ~/...
+        home_paths = re.findall(r"(?:^|[\s|>'\"])(~[^\s\"'>;|<]*)", command) # POSIX/Windows home shortcut: ~
-        return win_paths + posix_paths + tilde_paths
+        return win_paths + posix_paths + home_paths

nanobot/channels/base.py

@@ -1,6 +1,9 @@
 """Base channel interface for chat platforms."""
 
+from __future__ import annotations
+
 from abc import ABC, abstractmethod
+from pathlib import Path
 from typing import Any
 
 from loguru import logger
@@ -18,6 +21,8 @@ class BaseChannel(ABC):
     """
 
     name: str = "base"
+    display_name: str = "Base"
+    transcription_api_key: str = ""
 
     def __init__(self, config: Any, bus: MessageBus):
         """
@@ -31,6 +36,19 @@ class BaseChannel(ABC):
         self.bus = bus
         self._running = False
 
+    async def transcribe_audio(self, file_path: str | Path) -> str:
+        """Transcribe an audio file via Groq Whisper. Returns empty string on failure."""
+        if not self.transcription_api_key:
+            return ""
+        try:
+            from nanobot.providers.transcription import GroqTranscriptionProvider
+
+            provider = GroqTranscriptionProvider(api_key=self.transcription_api_key)
+            return await provider.transcribe(file_path)
+        except Exception as e:
+            logger.warning("{}: audio transcription failed: {}", self.name, e)
+            return ""
+
     @abstractmethod
     async def start(self) -> None:
         """
@@ -66,10 +84,7 @@ class BaseChannel(ABC):
             return False
         if "*" in allow_list:
             return True
-        sender_str = str(sender_id)
+        return str(sender_id) in allow_list
-        return sender_str in allow_list or any(
-            p in allow_list for p in sender_str.split("|") if p
-        )
 
     async def _handle_message(
         self,

nanobot/channels/dingtalk.py

@@ -57,6 +57,8 @@ class NanobotDingTalkHandler(CallbackHandler):
             content = ""
             if chatbot_msg.text:
                 content = chatbot_msg.text.content.strip()
+            elif chatbot_msg.extensions.get("content", {}).get("recognition"):
+                content = chatbot_msg.extensions["content"]["recognition"].strip()
             if not content:
                 content = message.data.get("text", {}).get("content", "").strip()
 
@@ -70,12 +72,24 @@ class NanobotDingTalkHandler(CallbackHandler):
             sender_id = chatbot_msg.sender_staff_id or chatbot_msg.sender_id
             sender_name = chatbot_msg.sender_nick or "Unknown"
 
+            conversation_type = message.data.get("conversationType")
+            conversation_id = (
+                message.data.get("conversationId")
+                or message.data.get("openConversationId")
+            )
+
             logger.info("Received DingTalk message from {} ({}): {}", sender_name, sender_id, content)
 
             # Forward to Nanobot via _on_message (non-blocking).
             # Store reference to prevent GC before task completes.
             task = asyncio.create_task(
-                self.channel._on_message(content, sender_id, sender_name)
+                self.channel._on_message(
+                    content,
+                    sender_id,
+                    sender_name,
+                    conversation_type,
+                    conversation_id,
+                )
             )
             self.channel._background_tasks.add(task)
             task.add_done_callback(self.channel._background_tasks.discard)
@@ -95,11 +109,12 @@ class DingTalkChannel(BaseChannel):
     Uses WebSocket to receive events via `dingtalk-stream` SDK.
     Uses direct HTTP API to send messages (SDK is mainly for receiving).
 
-    Note: Currently only supports private (1:1) chat. Group messages are
+    Supports both private (1:1) and group chats.
-    received but replies are sent back as private messages to the sender.
+    Group chat_id is stored with a "group:" prefix to route replies back.
     """
 
     name = "dingtalk"
+    display_name = "DingTalk"
     _IMAGE_EXTS = {".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp"}
     _AUDIO_EXTS = {".amr", ".mp3", ".wav", ".ogg", ".m4a", ".aac"}
     _VIDEO_EXTS = {".mp4", ".mov", ".avi", ".mkv", ".webm"}
@@ -301,14 +316,25 @@ class DingTalkChannel(BaseChannel):
             logger.warning("DingTalk HTTP client not initialized, cannot send")
             return False
 
-        url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
         headers = {"x-acs-dingtalk-access-token": token}
-        payload = {
+        if chat_id.startswith("group:"):
-            "robotCode": self.config.client_id,
+            # Group chat
-            "userIds": [chat_id],
+            url = "https://api.dingtalk.com/v1.0/robot/groupMessages/send"
-            "msgKey": msg_key,
+            payload = {
-            "msgParam": json.dumps(msg_param, ensure_ascii=False),
+                "robotCode": self.config.client_id,
-        }
+                "openConversationId": chat_id[6:],  # Remove "group:" prefix,
+                "msgKey": msg_key,
+                "msgParam": json.dumps(msg_param, ensure_ascii=False),
+            }
+        else:
+            # Private chat
+            url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
+            payload = {
+                "robotCode": self.config.client_id,
+                "userIds": [chat_id],
+                "msgKey": msg_key,
+                "msgParam": json.dumps(msg_param, ensure_ascii=False),
+            }
 
         try:
             resp = await self._http.post(url, json=payload, headers=headers)
@@ -417,7 +443,14 @@ class DingTalkChannel(BaseChannel):
                 f"[Attachment send failed: {filename}]",
             )
 
-    async def _on_message(self, content: str, sender_id: str, sender_name: str) -> None:
+    async def _on_message(
+        self,
+        content: str,
+        sender_id: str,
+        sender_name: str,
+        conversation_type: str | None = None,
+        conversation_id: str | None = None,
+    ) -> None:
         """Handle incoming message (called by NanobotDingTalkHandler).
 
         Delegates to BaseChannel._handle_message() which enforces allow_from
@@ -425,13 +458,16 @@ class DingTalkChannel(BaseChannel):
         """
         try:
             logger.info("DingTalk inbound: {} from {}", content, sender_name)
+            is_group = conversation_type == "2" and conversation_id
+            chat_id = f"group:{conversation_id}" if is_group else sender_id
             await self._handle_message(
                 sender_id=sender_id,
-                chat_id=sender_id,  # For private chat, chat_id == sender_id
+                chat_id=chat_id,
                 content=str(content),
                 metadata={
                     "sender_name": sender_name,
                     "platform": "dingtalk",
+                    "conversation_type": conversation_type,
                 },
             )
         except Exception as e:

nanobot/channels/discord.py

@@ -12,39 +12,20 @@ from loguru import logger
 from nanobot.bus.events import OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
+from nanobot.config.paths import get_media_dir
 from nanobot.config.schema import DiscordConfig
+from nanobot.utils.helpers import split_message
 
 DISCORD_API_BASE = "https://discord.com/api/v10"
 MAX_ATTACHMENT_BYTES = 20 * 1024 * 1024  # 20MB
 MAX_MESSAGE_LEN = 2000  # Discord message character limit
 
 
-def _split_message(content: str, max_len: int = MAX_MESSAGE_LEN) -> list[str]:
-    """Split content into chunks within max_len, preferring line breaks."""
-    if not content:
-        return []
-    if len(content) <= max_len:
-        return [content]
-    chunks: list[str] = []
-    while content:
-        if len(content) <= max_len:
-            chunks.append(content)
-            break
-        cut = content[:max_len]
-        pos = cut.rfind('\n')
-        if pos <= 0:
-            pos = cut.rfind(' ')
-        if pos <= 0:
-            pos = max_len
-        chunks.append(content[:pos])
-        content = content[pos:].lstrip()
-    return chunks
-
-
 class DiscordChannel(BaseChannel):
     """Discord channel using Gateway websocket."""
 
     name = "discord"
+    display_name = "Discord"
 
     def __init__(self, config: DiscordConfig, bus: MessageBus):
         super().__init__(config, bus)
@@ -54,6 +35,7 @@ class DiscordChannel(BaseChannel):
         self._heartbeat_task: asyncio.Task | None = None
         self._typing_tasks: dict[str, asyncio.Task] = {}
         self._http: httpx.AsyncClient | None = None
+        self._bot_user_id: str | None = None
 
     async def start(self) -> None:
         """Start the Discord gateway connection."""
@@ -95,7 +77,7 @@ class DiscordChannel(BaseChannel):
             self._http = None
 
     async def send(self, msg: OutboundMessage) -> None:
-        """Send a message through Discord REST API."""
+        """Send a message through Discord REST API, including file attachments."""
         if not self._http:
             logger.warning("Discord HTTP client not initialized")
             return
@@ -104,15 +86,31 @@ class DiscordChannel(BaseChannel):
         headers = {"Authorization": f"Bot {self.config.token}"}
 
         try:
-            chunks = _split_message(msg.content or "")
+            sent_media = False
+            failed_media: list[str] = []
+
+            # Send file attachments first
+            for media_path in msg.media or []:
+                if await self._send_file(url, headers, media_path, reply_to=msg.reply_to):
+                    sent_media = True
+                else:
+                    failed_media.append(Path(media_path).name)
+
+            # Send text content
+            chunks = split_message(msg.content or "", MAX_MESSAGE_LEN)
+            if not chunks and failed_media and not sent_media:
+                chunks = split_message(
+                    "\n".join(f"[attachment: {name} - send failed]" for name in failed_media),
+                    MAX_MESSAGE_LEN,
+                )
             if not chunks:
                 return
 
             for i, chunk in enumerate(chunks):
                 payload: dict[str, Any] = {"content": chunk}
 
-                # Only set reply reference on the first chunk
+                # Let the first successful attachment carry the reply if present.
-                if i == 0 and msg.reply_to:
+                if i == 0 and msg.reply_to and not sent_media:
                     payload["message_reference"] = {"message_id": msg.reply_to}
                     payload["allowed_mentions"] = {"replied_user": False}
 
@@ -143,6 +141,54 @@ class DiscordChannel(BaseChannel):
                     await asyncio.sleep(1)
         return False
 
+    async def _send_file(
+        self,
+        url: str,
+        headers: dict[str, str],
+        file_path: str,
+        reply_to: str | None = None,
+    ) -> bool:
+        """Send a file attachment via Discord REST API using multipart/form-data."""
+        path = Path(file_path)
+        if not path.is_file():
+            logger.warning("Discord file not found, skipping: {}", file_path)
+            return False
+
+        if path.stat().st_size > MAX_ATTACHMENT_BYTES:
+            logger.warning("Discord file too large (>20MB), skipping: {}", path.name)
+            return False
+
+        payload_json: dict[str, Any] = {}
+        if reply_to:
+            payload_json["message_reference"] = {"message_id": reply_to}
+            payload_json["allowed_mentions"] = {"replied_user": False}
+
+        for attempt in range(3):
+            try:
+                with open(path, "rb") as f:
+                    files = {"files[0]": (path.name, f, "application/octet-stream")}
+                    data: dict[str, Any] = {}
+                    if payload_json:
+                        data["payload_json"] = json.dumps(payload_json)
+                    response = await self._http.post(
+                        url, headers=headers, files=files, data=data
+                    )
+                if response.status_code == 429:
+                    resp_data = response.json()
+                    retry_after = float(resp_data.get("retry_after", 1.0))
+                    logger.warning("Discord rate limited, retrying in {}s", retry_after)
+                    await asyncio.sleep(retry_after)
+                    continue
+                response.raise_for_status()
+                logger.info("Discord file sent: {}", path.name)
+                return True
+            except Exception as e:
+                if attempt == 2:
+                    logger.error("Error sending Discord file {}: {}", path.name, e)
+                else:
+                    await asyncio.sleep(1)
+        return False
+
     async def _gateway_loop(self) -> None:
         """Main gateway loop: identify, heartbeat, dispatch events."""
         if not self._ws:
@@ -170,6 +216,10 @@ class DiscordChannel(BaseChannel):
                 await self._identify()
             elif op == 0 and event_type == "READY":
                 logger.info("Discord gateway READY")
+                # Capture bot user ID for mention detection
+                user_data = payload.get("user") or {}
+                self._bot_user_id = user_data.get("id")
+                logger.info("Discord bot connected as user {}", self._bot_user_id)
             elif op == 0 and event_type == "MESSAGE_CREATE":
                 await self._handle_message_create(payload)
             elif op == 7:
@@ -226,6 +276,7 @@ class DiscordChannel(BaseChannel):
         sender_id = str(author.get("id", ""))
         channel_id = str(payload.get("channel_id", ""))
         content = payload.get("content") or ""
+        guild_id = payload.get("guild_id")
 
         if not sender_id or not channel_id:
             return
@@ -233,9 +284,14 @@ class DiscordChannel(BaseChannel):
         if not self.is_allowed(sender_id):
             return
 
+        # Check group channel policy (DMs always respond if is_allowed passes)
+        if guild_id is not None:
+            if not self._should_respond_in_group(payload, content):
+                return
+
         content_parts = [content] if content else []
         media_paths: list[str] = []
-        media_dir = Path.home() / ".nanobot" / "media"
+        media_dir = get_media_dir("discord")
 
         for attachment in payload.get("attachments") or []:
             url = attachment.get("url")
@@ -269,11 +325,32 @@ class DiscordChannel(BaseChannel):
             media=media_paths,
             metadata={
                 "message_id": str(payload.get("id", "")),
-                "guild_id": payload.get("guild_id"),
+                "guild_id": guild_id,
                 "reply_to": reply_to,
             },
         )
 
+    def _should_respond_in_group(self, payload: dict[str, Any], content: str) -> bool:
+        """Check if bot should respond in a group channel based on policy."""
+        if self.config.group_policy == "open":
+            return True
+
+        if self.config.group_policy == "mention":
+            # Check if bot was mentioned in the message
+            if self._bot_user_id:
+                # Check mentions array
+                mentions = payload.get("mentions") or []
+                for mention in mentions:
+                    if str(mention.get("id")) == self._bot_user_id:
+                        return True
+                # Also check content for mention format <@USER_ID>
+                if f"<@{self._bot_user_id}>" in content or f"<@!{self._bot_user_id}>" in content:
+                    return True
+            logger.debug("Discord message in {} ignored (bot not mentioned)", payload.get("channel_id"))
+            return False
+
+        return True
+
     async def _start_typing(self, channel_id: str) -> None:
         """Start periodic typing indicator for a channel."""
         await self._stop_typing(channel_id)

nanobot/channels/email.py

@@ -35,6 +35,7 @@ class EmailChannel(BaseChannel):
     """
 
     name = "email"
+    display_name = "Email"
     _IMAP_MONTHS = (
         "Jan",
         "Feb",

nanobot/channels/feishu.py

@@ -14,28 +14,12 @@ from loguru import logger
 from nanobot.bus.events import OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
+from nanobot.config.paths import get_media_dir
 from nanobot.config.schema import FeishuConfig
 
-try:
+import importlib.util
-    import lark_oapi as lark
+
-    from lark_oapi.api.im.v1 import (
+FEISHU_AVAILABLE = importlib.util.find_spec("lark_oapi") is not None
-        CreateFileRequest,
-        CreateFileRequestBody,
-        CreateImageRequest,
-        CreateImageRequestBody,
-        CreateMessageReactionRequest,
-        CreateMessageReactionRequestBody,
-        CreateMessageRequest,
-        CreateMessageRequestBody,
-        Emoji,
-        GetMessageResourceRequest,
-        P2ImMessageReceiveV1,
-    )
-    FEISHU_AVAILABLE = True
-except ImportError:
-    FEISHU_AVAILABLE = False
-    lark = None
-    Emoji = None
 
 # Message type display mapping
 MSG_TYPE_MAP = {
@@ -260,6 +244,7 @@ class FeishuChannel(BaseChannel):
     """
 
     name = "feishu"
+    display_name = "Feishu"
 
     def __init__(self, config: FeishuConfig, bus: MessageBus):
         super().__init__(config, bus)
@@ -270,6 +255,12 @@ class FeishuChannel(BaseChannel):
         self._processed_message_ids: OrderedDict[str, None] = OrderedDict()  # Ordered dedup cache
         self._loop: asyncio.AbstractEventLoop | None = None
 
+    @staticmethod
+    def _register_optional_event(builder: Any, method_name: str, handler: Any) -> Any:
+        """Register an event handler only when the SDK supports it."""
+        method = getattr(builder, method_name, None)
+        return method(handler) if callable(method) else builder
+
     async def start(self) -> None:
         """Start the Feishu bot with WebSocket long connection."""
         if not FEISHU_AVAILABLE:
@@ -280,6 +271,7 @@ class FeishuChannel(BaseChannel):
             logger.error("Feishu app_id and app_secret not configured")
             return
 
+        import lark_oapi as lark
         self._running = True
         self._loop = asyncio.get_running_loop()
 
@@ -289,14 +281,24 @@ class FeishuChannel(BaseChannel):
             .app_secret(self.config.app_secret) \
             .log_level(lark.LogLevel.INFO) \
             .build()
-
+        builder = lark.EventDispatcherHandler.builder(
-        # Create event handler (only register message receive, ignore other events)
-        event_handler = lark.EventDispatcherHandler.builder(
             self.config.encrypt_key or "",
             self.config.verification_token or "",
         ).register_p2_im_message_receive_v1(
             self._on_message_sync
-        ).build()
+        )
+        builder = self._register_optional_event(
+            builder, "register_p2_im_message_reaction_created_v1", self._on_reaction_created
+        )
+        builder = self._register_optional_event(
+            builder, "register_p2_im_message_message_read_v1", self._on_message_read
+        )
+        builder = self._register_optional_event(
+            builder,
+            "register_p2_im_chat_access_event_bot_p2p_chat_entered_v1",
+            self._on_bot_p2p_chat_entered,
+        )
+        event_handler = builder.build()
 
         # Create WebSocket client for long connection
         self._ws_client = lark.ws.Client(
@@ -306,16 +308,28 @@ class FeishuChannel(BaseChannel):
             log_level=lark.LogLevel.INFO
         )
 
-        # Start WebSocket client in a separate thread with reconnect loop
+        # Start WebSocket client in a separate thread with reconnect loop.
+        # A dedicated event loop is created for this thread so that lark_oapi's
+        # module-level `loop = asyncio.get_event_loop()` picks up an idle loop
+        # instead of the already-running main asyncio loop, which would cause
+        # "This event loop is already running" errors.
         def run_ws():
-            while self._running:
+            import time
-                try:
+            import lark_oapi.ws.client as _lark_ws_client
-                    self._ws_client.start()
+            ws_loop = asyncio.new_event_loop()
-                except Exception as e:
+            asyncio.set_event_loop(ws_loop)
-                    logger.warning("Feishu WebSocket error: {}", e)
+            # Patch the module-level loop used by lark's ws Client.start()
-                if self._running:
+            _lark_ws_client.loop = ws_loop
-                    import time
+            try:
-                    time.sleep(5)
+                while self._running:
+                    try:
+                        self._ws_client.start()
+                    except Exception as e:
+                        logger.warning("Feishu WebSocket error: {}", e)
+                    if self._running:
+                        time.sleep(5)
+            finally:
+                ws_loop.close()
 
         self._ws_thread = threading.Thread(target=run_ws, daemon=True)
         self._ws_thread.start()
@@ -340,6 +354,7 @@ class FeishuChannel(BaseChannel):
 
     def _add_reaction_sync(self, message_id: str, emoji_type: str) -> None:
         """Sync helper for adding reaction (runs in thread pool)."""
+        from lark_oapi.api.im.v1 import CreateMessageReactionRequest, CreateMessageReactionRequestBody, Emoji
         try:
             request = CreateMessageReactionRequest.builder() \
                 .message_id(message_id) \
@@ -364,7 +379,7 @@ class FeishuChannel(BaseChannel):
 
         Common emoji types: THUMBSUP, OK, EYES, DONE, OnIt, HEART
         """
-        if not self._client or not Emoji:
+        if not self._client:
             return
 
         loop = asyncio.get_running_loop()
@@ -413,6 +428,34 @@ class FeishuChannel(BaseChannel):
             elements.extend(self._split_headings(remaining))
         return elements or [{"tag": "markdown", "content": content}]
 
+    @staticmethod
+    def _split_elements_by_table_limit(elements: list[dict], max_tables: int = 1) -> list[list[dict]]:
+        """Split card elements into groups with at most *max_tables* table elements each.
+
+        Feishu cards have a hard limit of one table per card (API error 11310).
+        When the rendered content contains multiple markdown tables each table is
+        placed in a separate card message so every table reaches the user.
+        """
+        if not elements:
+            return [[]]
+        groups: list[list[dict]] = []
+        current: list[dict] = []
+        table_count = 0
+        for el in elements:
+            if el.get("tag") == "table":
+                if table_count >= max_tables:
+                    if current:
+                        groups.append(current)
+                    current = []
+                    table_count = 0
+                current.append(el)
+                table_count += 1
+            else:
+                current.append(el)
+        if current:
+            groups.append(current)
+        return groups or [[]]
+
     def _split_headings(self, content: str) -> list[dict]:
         """Split content by headings, converting headings to div elements."""
         protected = content
@@ -447,8 +490,124 @@ class FeishuChannel(BaseChannel):
 
         return elements or [{"tag": "markdown", "content": content}]
 
+    # ── Smart format detection ──────────────────────────────────────────
+    # Patterns that indicate "complex" markdown needing card rendering
+    _COMPLEX_MD_RE = re.compile(
+        r"```"                        # fenced code block
+        r"|^\|.+\|.*\n\s*\|[-:\s|]+\|"  # markdown table (header + separator)
+        r"|^#{1,6}\s+"                # headings
+        , re.MULTILINE,
+    )
+
+    # Simple markdown patterns (bold, italic, strikethrough)
+    _SIMPLE_MD_RE = re.compile(
+        r"\*\*.+?\*\*"               # **bold**
+        r"|__.+?__"                   # __bold__
+        r"|(?<!\*)\*(?!\*)(.+?)(?<!\*)\*(?!\*)"  # *italic* (single *)
+        r"|~~.+?~~"                   # ~~strikethrough~~
+        , re.DOTALL,
+    )
+
+    # Markdown link: [text](url)
+    _MD_LINK_RE = re.compile(r"\[([^\]]+)\]\((https?://[^\)]+)\)")
+
+    # Unordered list items
+    _LIST_RE = re.compile(r"^[\s]*[-*+]\s+", re.MULTILINE)
+
+    # Ordered list items
+    _OLIST_RE = re.compile(r"^[\s]*\d+\.\s+", re.MULTILINE)
+
+    # Max length for plain text format
+    _TEXT_MAX_LEN = 200
+
+    # Max length for post (rich text) format; beyond this, use card
+    _POST_MAX_LEN = 2000
+
+    @classmethod
+    def _detect_msg_format(cls, content: str) -> str:
+        """Determine the optimal Feishu message format for *content*.
+
+        Returns one of:
+        - ``"text"``        – plain text, short and no markdown
+        - ``"post"``        – rich text (links only, moderate length)
+        - ``"interactive"`` – card with full markdown rendering
+        """
+        stripped = content.strip()
+
+        # Complex markdown (code blocks, tables, headings) → always card
+        if cls._COMPLEX_MD_RE.search(stripped):
+            return "interactive"
+
+        # Long content → card (better readability with card layout)
+        if len(stripped) > cls._POST_MAX_LEN:
+            return "interactive"
+
+        # Has bold/italic/strikethrough → card (post format can't render these)
+        if cls._SIMPLE_MD_RE.search(stripped):
+            return "interactive"
+
+        # Has list items → card (post format can't render list bullets well)
+        if cls._LIST_RE.search(stripped) or cls._OLIST_RE.search(stripped):
+            return "interactive"
+
+        # Has links → post format (supports <a> tags)
+        if cls._MD_LINK_RE.search(stripped):
+            return "post"
+
+        # Short plain text → text format
+        if len(stripped) <= cls._TEXT_MAX_LEN:
+            return "text"
+
+        # Medium plain text without any formatting → post format
+        return "post"
+
+    @classmethod
+    def _markdown_to_post(cls, content: str) -> str:
+        """Convert markdown content to Feishu post message JSON.
+
+        Handles links ``[text](url)`` as ``a`` tags; everything else as ``text`` tags.
+        Each line becomes a paragraph (row) in the post body.
+        """
+        lines = content.strip().split("\n")
+        paragraphs: list[list[dict]] = []
+
+        for line in lines:
+            elements: list[dict] = []
+            last_end = 0
+
+            for m in cls._MD_LINK_RE.finditer(line):
+                # Text before this link
+                before = line[last_end:m.start()]
+                if before:
+                    elements.append({"tag": "text", "text": before})
+                elements.append({
+                    "tag": "a",
+                    "text": m.group(1),
+                    "href": m.group(2),
+                })
+                last_end = m.end()
+
+            # Remaining text after last link
+            remaining = line[last_end:]
+            if remaining:
+                elements.append({"tag": "text", "text": remaining})
+
+            # Empty line → empty paragraph for spacing
+            if not elements:
+                elements.append({"tag": "text", "text": ""})
+
+            paragraphs.append(elements)
+
+        post_body = {
+            "zh_cn": {
+                "content": paragraphs,
+            }
+        }
+        return json.dumps(post_body, ensure_ascii=False)
+
     _IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".gif", ".bmp", ".webp", ".ico", ".tiff", ".tif"}
     _AUDIO_EXTS = {".opus"}
+    _VIDEO_EXTS = {".mp4", ".mov", ".avi"}
     _FILE_TYPE_MAP = {
         ".opus": "opus", ".mp4": "mp4", ".pdf": "pdf", ".doc": "doc", ".docx": "doc",
         ".xls": "xls", ".xlsx": "xls", ".ppt": "ppt", ".pptx": "ppt",
@@ -456,6 +615,7 @@ class FeishuChannel(BaseChannel):
 
     def _upload_image_sync(self, file_path: str) -> str | None:
         """Upload an image to Feishu and return the image_key."""
+        from lark_oapi.api.im.v1 import CreateImageRequest, CreateImageRequestBody
         try:
             with open(file_path, "rb") as f:
                 request = CreateImageRequest.builder() \
@@ -479,6 +639,7 @@ class FeishuChannel(BaseChannel):
 
     def _upload_file_sync(self, file_path: str) -> str | None:
         """Upload a file to Feishu and return the file_key."""
+        from lark_oapi.api.im.v1 import CreateFileRequest, CreateFileRequestBody
         ext = os.path.splitext(file_path)[1].lower()
         file_type = self._FILE_TYPE_MAP.get(ext, "stream")
         file_name = os.path.basename(file_path)
@@ -506,6 +667,7 @@ class FeishuChannel(BaseChannel):
 
     def _download_image_sync(self, message_id: str, image_key: str) -> tuple[bytes | None, str | None]:
         """Download an image from Feishu message by message_id and image_key."""
+        from lark_oapi.api.im.v1 import GetMessageResourceRequest
         try:
             request = GetMessageResourceRequest.builder() \
                 .message_id(message_id) \
@@ -530,6 +692,13 @@ class FeishuChannel(BaseChannel):
         self, message_id: str, file_key: str, resource_type: str = "file"
     ) -> tuple[bytes | None, str | None]:
         """Download a file/audio/media from a Feishu message by message_id and file_key."""
+        from lark_oapi.api.im.v1 import GetMessageResourceRequest
+
+        # Feishu API only accepts 'image' or 'file' as type parameter
+        # Convert 'audio' to 'file' for API compatibility
+        if resource_type == "audio":
+            resource_type = "file"
+
         try:
             request = (
                 GetMessageResourceRequest.builder()
@@ -564,8 +733,7 @@ class FeishuChannel(BaseChannel):
             (file_path, content_text) - file_path is None if download failed
         """
         loop = asyncio.get_running_loop()
-        media_dir = Path.home() / ".nanobot" / "media"
+        media_dir = get_media_dir("feishu")
-        media_dir.mkdir(parents=True, exist_ok=True)
 
         data, filename = None, None
 
@@ -585,8 +753,9 @@ class FeishuChannel(BaseChannel):
                     None, self._download_file_sync, message_id, file_key, msg_type
                 )
                 if not filename:
-                    ext = {"audio": ".opus", "media": ".mp4"}.get(msg_type, "")
+                    filename = file_key[:16]
-                    filename = f"{file_key[:16]}{ext}"
+                if msg_type == "audio" and not filename.endswith(".opus"):
+                    filename = f"{filename}.opus"
 
         if data and filename:
             file_path = media_dir / filename
@@ -598,6 +767,7 @@ class FeishuChannel(BaseChannel):
 
     def _send_message_sync(self, receive_id_type: str, receive_id: str, msg_type: str, content: str) -> bool:
         """Send a single message (text/image/file/interactive) synchronously."""
+        from lark_oapi.api.im.v1 import CreateMessageRequest, CreateMessageRequestBody
         try:
             request = CreateMessageRequest.builder() \
                 .receive_id_type(receive_id_type) \
@@ -646,23 +816,50 @@ class FeishuChannel(BaseChannel):
                 else:
                     key = await loop.run_in_executor(None, self._upload_file_sync, file_path)
                     if key:
-                        media_type = "audio" if ext in self._AUDIO_EXTS else "file"
+                        # Use msg_type "media" for audio/video so users can play inline;
+                        # "file" for everything else (documents, archives, etc.)
+                        if ext in self._AUDIO_EXTS or ext in self._VIDEO_EXTS:
+                            media_type = "media"
+                        else:
+                            media_type = "file"
                         await loop.run_in_executor(
                             None, self._send_message_sync,
                             receive_id_type, msg.chat_id, media_type, json.dumps({"file_key": key}, ensure_ascii=False),
                         )
 
             if msg.content and msg.content.strip():
-                card = {"config": {"wide_screen_mode": True}, "elements": self._build_card_elements(msg.content)}
+                fmt = self._detect_msg_format(msg.content)
-                await loop.run_in_executor(
+
-                    None, self._send_message_sync,
+                if fmt == "text":
-                    receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False),
+                    # Short plain text – send as simple text message
-                )
+                    text_body = json.dumps({"text": msg.content.strip()}, ensure_ascii=False)
+                    await loop.run_in_executor(
+                        None, self._send_message_sync,
+                        receive_id_type, msg.chat_id, "text", text_body,
+                    )
+
+                elif fmt == "post":
+                    # Medium content with links – send as rich-text post
+                    post_body = self._markdown_to_post(msg.content)
+                    await loop.run_in_executor(
+                        None, self._send_message_sync,
+                        receive_id_type, msg.chat_id, "post", post_body,
+                    )
+
+                else:
+                    # Complex / long content – send as interactive card
+                    elements = self._build_card_elements(msg.content)
+                    for chunk in self._split_elements_by_table_limit(elements):
+                        card = {"config": {"wide_screen_mode": True}, "elements": chunk}
+                        await loop.run_in_executor(
+                            None, self._send_message_sync,
+                            receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False),
+                        )
 
         except Exception as e:
             logger.error("Error sending Feishu message: {}", e)
 
-    def _on_message_sync(self, data: "P2ImMessageReceiveV1") -> None:
+    def _on_message_sync(self, data: Any) -> None:
         """
         Sync handler for incoming messages (called from WebSocket thread).
         Schedules async handling in the main event loop.
@@ -670,7 +867,7 @@ class FeishuChannel(BaseChannel):
         if self._loop and self._loop.is_running():
             asyncio.run_coroutine_threadsafe(self._on_message(data), self._loop)
 
-    async def _on_message(self, data: "P2ImMessageReceiveV1") -> None:
+    async def _on_message(self, data: Any) -> None:
         """Handle incoming message from Feishu."""
         try:
             event = data.event
@@ -730,6 +927,12 @@ class FeishuChannel(BaseChannel):
                 file_path, content_text = await self._download_and_save_media(msg_type, content_json, message_id)
                 if file_path:
                     media_paths.append(file_path)
+
+                if msg_type == "audio" and file_path:
+                    transcription = await self.transcribe_audio(file_path)
+                    if transcription:
+                        content_text = f"[transcription: {transcription}]"
+
                 content_parts.append(content_text)
 
             elif msg_type in ("share_chat", "share_user", "interactive", "share_calendar_event", "system", "merge_forward"):
@@ -762,3 +965,16 @@ class FeishuChannel(BaseChannel):
 
         except Exception as e:
             logger.error("Error processing Feishu message: {}", e)
+
+    def _on_reaction_created(self, data: Any) -> None:
+        """Ignore reaction events so they do not generate SDK noise."""
+        pass
+
+    def _on_message_read(self, data: Any) -> None:
+        """Ignore read events so they do not generate SDK noise."""
+        pass
+
+    def _on_bot_p2p_chat_entered(self, data: Any) -> None:
+        """Ignore p2p-enter events when a user opens a bot chat."""
+        logger.debug("Bot entered p2p chat (user opened chat window)")
+        pass

nanobot/channels/manager.py

@@ -7,7 +7,6 @@ from typing import Any
 
 from loguru import logger
 
-from nanobot.bus.events import OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
 from nanobot.config.schema import Config
@@ -32,122 +31,23 @@ class ChannelManager:
         self._init_channels()
 
     def _init_channels(self) -> None:
-        """Initialize channels based on config."""
+        """Initialize channels discovered via pkgutil scan."""
+        from nanobot.channels.registry import discover_channel_names, load_channel_class
 
-        # Telegram channel
+        groq_key = self.config.providers.groq.api_key
-        if self.config.channels.telegram.enabled:
+
+        for modname in discover_channel_names():
+            section = getattr(self.config.channels, modname, None)
+            if not section or not getattr(section, "enabled", False):
+                continue
             try:
-                from nanobot.channels.telegram import TelegramChannel
+                cls = load_channel_class(modname)
-                self.channels["telegram"] = TelegramChannel(
+                channel = cls(section, self.bus)
-                    self.config.channels.telegram,
+                channel.transcription_api_key = groq_key
-                    self.bus,
+                self.channels[modname] = channel
-                    groq_api_key=self.config.providers.groq.api_key,
+                logger.info("{} channel enabled", cls.display_name)
-                )
-                logger.info("Telegram channel enabled")
             except ImportError as e:
-                logger.warning("Telegram channel not available: {}", e)
+                logger.warning("{} channel not available: {}", modname, e)
-
-        # WhatsApp channel
-        if self.config.channels.whatsapp.enabled:
-            try:
-                from nanobot.channels.whatsapp import WhatsAppChannel
-                self.channels["whatsapp"] = WhatsAppChannel(
-                    self.config.channels.whatsapp, self.bus
-                )
-                logger.info("WhatsApp channel enabled")
-            except ImportError as e:
-                logger.warning("WhatsApp channel not available: {}", e)
-
-        # Discord channel
-        if self.config.channels.discord.enabled:
-            try:
-                from nanobot.channels.discord import DiscordChannel
-                self.channels["discord"] = DiscordChannel(
-                    self.config.channels.discord, self.bus
-                )
-                logger.info("Discord channel enabled")
-            except ImportError as e:
-                logger.warning("Discord channel not available: {}", e)
-
-        # Feishu channel
-        if self.config.channels.feishu.enabled:
-            try:
-                from nanobot.channels.feishu import FeishuChannel
-                self.channels["feishu"] = FeishuChannel(
-                    self.config.channels.feishu, self.bus
-                )
-                logger.info("Feishu channel enabled")
-            except ImportError as e:
-                logger.warning("Feishu channel not available: {}", e)
-
-        # Mochat channel
-        if self.config.channels.mochat.enabled:
-            try:
-                from nanobot.channels.mochat import MochatChannel
-
-                self.channels["mochat"] = MochatChannel(
-                    self.config.channels.mochat, self.bus
-                )
-                logger.info("Mochat channel enabled")
-            except ImportError as e:
-                logger.warning("Mochat channel not available: {}", e)
-
-        # DingTalk channel
-        if self.config.channels.dingtalk.enabled:
-            try:
-                from nanobot.channels.dingtalk import DingTalkChannel
-                self.channels["dingtalk"] = DingTalkChannel(
-                    self.config.channels.dingtalk, self.bus
-                )
-                logger.info("DingTalk channel enabled")
-            except ImportError as e:
-                logger.warning("DingTalk channel not available: {}", e)
-
-        # Email channel
-        if self.config.channels.email.enabled:
-            try:
-                from nanobot.channels.email import EmailChannel
-                self.channels["email"] = EmailChannel(
-                    self.config.channels.email, self.bus
-                )
-                logger.info("Email channel enabled")
-            except ImportError as e:
-                logger.warning("Email channel not available: {}", e)
-
-        # Slack channel
-        if self.config.channels.slack.enabled:
-            try:
-                from nanobot.channels.slack import SlackChannel
-                self.channels["slack"] = SlackChannel(
-                    self.config.channels.slack, self.bus
-                )
-                logger.info("Slack channel enabled")
-            except ImportError as e:
-                logger.warning("Slack channel not available: {}", e)
-
-        # QQ channel
-        if self.config.channels.qq.enabled:
-            try:
-                from nanobot.channels.qq import QQChannel
-                self.channels["qq"] = QQChannel(
-                    self.config.channels.qq,
-                    self.bus,
-                )
-                logger.info("QQ channel enabled")
-            except ImportError as e:
-                logger.warning("QQ channel not available: {}", e)
-
-        # Matrix channel
-        if self.config.channels.matrix.enabled:
-            try:
-                from nanobot.channels.matrix import MatrixChannel
-                self.channels["matrix"] = MatrixChannel(
-                    self.config.channels.matrix,
-                    self.bus,
-                )
-                logger.info("Matrix channel enabled")
-            except ImportError as e:
-                logger.warning("Matrix channel not available: {}", e)
 
         self._validate_allow_from()
 

nanobot/channels/matrix.py

@@ -37,8 +37,9 @@ except ImportError as e:
     ) from e
 
 from nanobot.bus.events import OutboundMessage
+from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
-from nanobot.config.loader import get_data_dir
+from nanobot.config.paths import get_data_dir, get_media_dir
 from nanobot.utils.helpers import safe_filename
 
 TYPING_NOTICE_TIMEOUT_MS = 30_000
@@ -146,15 +147,15 @@ class MatrixChannel(BaseChannel):
     """Matrix (Element) channel using long-polling sync."""
 
     name = "matrix"
+    display_name = "Matrix"
 
-    def __init__(self, config: Any, bus, *, restrict_to_workspace: bool = False,
+    def __init__(self, config: Any, bus: MessageBus):
-                 workspace: Path | None = None):
         super().__init__(config, bus)
         self.client: AsyncClient | None = None
         self._sync_task: asyncio.Task | None = None
         self._typing_tasks: dict[str, asyncio.Task] = {}
-        self._restrict_to_workspace = restrict_to_workspace
+        self._restrict_to_workspace = False
-        self._workspace = workspace.expanduser().resolve() if workspace else None
+        self._workspace: Path | None = None
         self._server_upload_limit_bytes: int | None = None
         self._server_upload_limit_checked = False
 
@@ -490,9 +491,7 @@ class MatrixChannel(BaseChannel):
         return False
 
     def _media_dir(self) -> Path:
-        d = get_data_dir() / "media" / "matrix"
+        return get_media_dir("matrix")
-        d.mkdir(parents=True, exist_ok=True)
-        return d
 
     @staticmethod
     def _event_source_content(event: RoomMessage) -> dict[str, Any]:
@@ -679,7 +678,14 @@ class MatrixChannel(BaseChannel):
         parts: list[str] = []
         if isinstance(body := getattr(event, "body", None), str) and body.strip():
             parts.append(body.strip())
-        if marker:
+
+        if attachment and attachment.get("type") == "audio":
+            transcription = await self.transcribe_audio(attachment["path"])
+            if transcription:
+                parts.append(f"[transcription: {transcription}]")
+            else:
+                parts.append(marker)
+        elif marker:
             parts.append(marker)
 
         await self._start_typing_keepalive(room.room_id)

nanobot/channels/mochat.py

@@ -15,8 +15,8 @@ from loguru import logger
 from nanobot.bus.events import OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
+from nanobot.config.paths import get_runtime_subdir
 from nanobot.config.schema import MochatConfig
-from nanobot.utils.helpers import get_data_path
 
 try:
     import socketio
@@ -216,6 +216,7 @@ class MochatChannel(BaseChannel):
     """Mochat channel using socket.io with fallback polling workers."""
 
     name = "mochat"
+    display_name = "Mochat"
 
     def __init__(self, config: MochatConfig, bus: MessageBus):
         super().__init__(config, bus)
@@ -224,7 +225,7 @@ class MochatChannel(BaseChannel):
         self._socket: Any = None
         self._ws_connected = self._ws_ready = False
 
-        self._state_dir = get_data_path() / "mochat"
+        self._state_dir = get_runtime_subdir("mochat")
         self._cursor_path = self._state_dir / "session_cursors.json"
         self._session_cursor: dict[str, int] = {}
         self._cursor_save_task: asyncio.Task | None = None

nanobot/channels/qq.py

@@ -13,16 +13,17 @@ from nanobot.config.schema import QQConfig
 
 try:
     import botpy
-    from botpy.message import C2CMessage
+    from botpy.message import C2CMessage, GroupMessage
 
     QQ_AVAILABLE = True
 except ImportError:
     QQ_AVAILABLE = False
     botpy = None
     C2CMessage = None
+    GroupMessage = None
 
 if TYPE_CHECKING:
-    from botpy.message import C2CMessage
+    from botpy.message import C2CMessage, GroupMessage
 
 
 def _make_bot_class(channel: "QQChannel") -> "type[botpy.Client]":
@@ -38,10 +39,13 @@ def _make_bot_class(channel: "QQChannel") -> "type[botpy.Client]":
             logger.info("QQ bot ready: {}", self.robot.name)
 
         async def on_c2c_message_create(self, message: "C2CMessage"):
-            await channel._on_message(message)
+            await channel._on_message(message, is_group=False)
+
+        async def on_group_at_message_create(self, message: "GroupMessage"):
+            await channel._on_message(message, is_group=True)
 
         async def on_direct_message_create(self, message):
-            await channel._on_message(message)
+            await channel._on_message(message, is_group=False)
 
     return _Bot
 
@@ -50,12 +54,15 @@ class QQChannel(BaseChannel):
     """QQ channel using botpy SDK with WebSocket connection."""
 
     name = "qq"
+    display_name = "QQ"
 
     def __init__(self, config: QQConfig, bus: MessageBus):
         super().__init__(config, bus)
         self.config: QQConfig = config
         self._client: "botpy.Client | None" = None
         self._processed_ids: deque = deque(maxlen=1000)
+        self._msg_seq: int = 1  # 消息序列号，避免被 QQ API 去重
+        self._chat_type_cache: dict[str, str] = {}
 
     async def start(self) -> None:
         """Start the QQ bot."""
@@ -70,8 +77,7 @@ class QQChannel(BaseChannel):
         self._running = True
         BotClass = _make_bot_class(self)
         self._client = BotClass()
-
+        logger.info("QQ bot started (C2C & Group supported)")
-        logger.info("QQ bot started (C2C private message)")
         await self._run_bot()
 
     async def _run_bot(self) -> None:
@@ -100,18 +106,31 @@ class QQChannel(BaseChannel):
         if not self._client:
             logger.warning("QQ client not initialized")
             return
+
         try:
             msg_id = msg.metadata.get("message_id")
-            await self._client.api.post_c2c_message(
+            self._msg_seq += 1
-                openid=msg.chat_id,
+            msg_type = self._chat_type_cache.get(msg.chat_id, "c2c")
-                msg_type=0,
+            if msg_type == "group":
-                content=msg.content,
+                await self._client.api.post_group_message(
-                msg_id=msg_id,
+                    group_openid=msg.chat_id,
-            )
+                    msg_type=2,
+                    markdown={"content": msg.content},
+                    msg_id=msg_id,
+                    msg_seq=self._msg_seq,
+                )
+            else:
+                await self._client.api.post_c2c_message(
+                    openid=msg.chat_id,
+                    msg_type=2,
+                    markdown={"content": msg.content},
+                    msg_id=msg_id,
+                    msg_seq=self._msg_seq,
+                )
         except Exception as e:
             logger.error("Error sending QQ message: {}", e)
 
-    async def _on_message(self, data: "C2CMessage") -> None:
+    async def _on_message(self, data: "C2CMessage | GroupMessage", is_group: bool = False) -> None:
         """Handle incoming message from QQ."""
         try:
             # Dedup by message ID
@@ -119,15 +138,22 @@ class QQChannel(BaseChannel):
                 return
             self._processed_ids.append(data.id)
 
-            author = data.author
-            user_id = str(getattr(author, 'id', None) or getattr(author, 'user_openid', 'unknown'))
             content = (data.content or "").strip()
             if not content:
                 return
 
+            if is_group:
+                chat_id = data.group_openid
+                user_id = data.author.member_openid
+                self._chat_type_cache[chat_id] = "group"
+            else:
+                chat_id = str(getattr(data.author, 'id', None) or getattr(data.author, 'user_openid', 'unknown'))
+                user_id = chat_id
+                self._chat_type_cache[chat_id] = "c2c"
+
             await self._handle_message(
                 sender_id=user_id,
-                chat_id=user_id,
+                chat_id=chat_id,
                 content=content,
                 metadata={"message_id": data.id},
             )

nanobot/channels/registry.py

@@ -0,0 +1,35 @@
+"""Auto-discovery for channel modules — no hardcoded registry."""
+
+from __future__ import annotations
+
+import importlib
+import pkgutil
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from nanobot.channels.base import BaseChannel
+
+_INTERNAL = frozenset({"base", "manager", "registry"})
+
+
+def discover_channel_names() -> list[str]:
+    """Return all channel module names by scanning the package (zero imports)."""
+    import nanobot.channels as pkg
+
+    return [
+        name
+        for _, name, ispkg in pkgutil.iter_modules(pkg.__path__)
+        if name not in _INTERNAL and not ispkg
+    ]
+
+
+def load_channel_class(module_name: str) -> type[BaseChannel]:
+    """Import *module_name* and return the first BaseChannel subclass found."""
+    from nanobot.channels.base import BaseChannel as _Base
+
+    mod = importlib.import_module(f"nanobot.channels.{module_name}")
+    for attr in dir(mod):
+        obj = getattr(mod, attr)
+        if isinstance(obj, type) and issubclass(obj, _Base) and obj is not _Base:
+            return obj
+    raise ImportError(f"No BaseChannel subclass in nanobot.channels.{module_name}")

nanobot/channels/slack.py

@@ -21,6 +21,7 @@ class SlackChannel(BaseChannel):
     """Slack channel using Socket Mode."""
 
     name = "slack"
+    display_name = "Slack"
 
     def __init__(self, config: SlackConfig, bus: MessageBus):
         super().__init__(config, bus)
@@ -81,14 +82,15 @@ class SlackChannel(BaseChannel):
             slack_meta = msg.metadata.get("slack", {}) if msg.metadata else {}
             thread_ts = slack_meta.get("thread_ts")
             channel_type = slack_meta.get("channel_type")
-            # Only reply in thread for channel/group messages; DMs don't use threads
+            # Slack DMs don't use threads; channel/group replies may keep thread_ts.
-            use_thread = thread_ts and channel_type != "im"
+            thread_ts_param = thread_ts if thread_ts and channel_type != "im" else None
-            thread_ts_param = thread_ts if use_thread else None
 
-            if msg.content:
+            # Slack rejects empty text payloads. Keep media-only messages media-only,
+            # but send a single blank message when the bot has no text or files to send.
+            if msg.content or not (msg.media or []):
                 await self._web_client.chat_postMessage(
                     channel=msg.chat_id,
-                    text=self._to_mrkdwn(msg.content),
+                    text=self._to_mrkdwn(msg.content) if msg.content else " ",
                     thread_ts=thread_ts_param,
                 )
 
@@ -277,4 +279,3 @@ class SlackChannel(BaseChannel):
             if parts:
                 rows.append(" · ".join(parts))
         return "\n".join(rows)
-

nanobot/channels/telegram.py

@@ -4,6 +4,8 @@ from __future__ import annotations
 
 import asyncio
 import re
+import time
+import unicodedata
 
 from loguru import logger
 from telegram import BotCommand, ReplyParameters, Update
@@ -13,7 +15,52 @@ from telegram.request import HTTPXRequest
 from nanobot.bus.events import OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
+from nanobot.config.paths import get_media_dir
 from nanobot.config.schema import TelegramConfig
+from nanobot.utils.helpers import split_message
+
+TELEGRAM_MAX_MESSAGE_LEN = 4000  # Telegram message character limit
+
+
+def _strip_md(s: str) -> str:
+    """Strip markdown inline formatting from text."""
+    s = re.sub(r'\*\*(.+?)\*\*', r'\1', s)
+    s = re.sub(r'__(.+?)__', r'\1', s)
+    s = re.sub(r'~~(.+?)~~', r'\1', s)
+    s = re.sub(r'`([^`]+)`', r'\1', s)
+    return s.strip()
+
+
+def _render_table_box(table_lines: list[str]) -> str:
+    """Convert markdown pipe-table to compact aligned text for <pre> display."""
+
+    def dw(s: str) -> int:
+        return sum(2 if unicodedata.east_asian_width(c) in ('W', 'F') else 1 for c in s)
+
+    rows: list[list[str]] = []
+    has_sep = False
+    for line in table_lines:
+        cells = [_strip_md(c) for c in line.strip().strip('|').split('|')]
+        if all(re.match(r'^:?-+:?$', c) for c in cells if c):
+            has_sep = True
+            continue
+        rows.append(cells)
+    if not rows or not has_sep:
+        return '\n'.join(table_lines)
+
+    ncols = max(len(r) for r in rows)
+    for r in rows:
+        r.extend([''] * (ncols - len(r)))
+    widths = [max(dw(r[c]) for r in rows) for c in range(ncols)]
+
+    def dr(cells: list[str]) -> str:
+        return '  '.join(f'{c}{" " * (w - dw(c))}' for c, w in zip(cells, widths))
+
+    out = [dr(rows[0])]
+    out.append('  '.join('─' * w for w in widths))
+    for row in rows[1:]:
+        out.append(dr(row))
+    return '\n'.join(out)
 
 
 def _markdown_to_telegram_html(text: str) -> str:
@@ -31,6 +78,27 @@ def _markdown_to_telegram_html(text: str) -> str:
 
     text = re.sub(r'```[\w]*\n?([\s\S]*?)```', save_code_block, text)
 
+    # 1.5. Convert markdown tables to box-drawing (reuse code_block placeholders)
+    lines = text.split('\n')
+    rebuilt: list[str] = []
+    li = 0
+    while li < len(lines):
+        if re.match(r'^\s*\|.+\|', lines[li]):
+            tbl: list[str] = []
+            while li < len(lines) and re.match(r'^\s*\|.+\|', lines[li]):
+                tbl.append(lines[li])
+                li += 1
+            box = _render_table_box(tbl)
+            if box != '\n'.join(tbl):
+                code_blocks.append(box)
+                rebuilt.append(f"\x00CB{len(code_blocks) - 1}\x00")
+            else:
+                rebuilt.extend(tbl)
+        else:
+            rebuilt.append(lines[li])
+            li += 1
+    text = '\n'.join(rebuilt)
+
     # 2. Extract and protect inline code
     inline_codes: list[str] = []
     def save_inline_code(m: re.Match) -> str:
@@ -79,26 +147,6 @@ def _markdown_to_telegram_html(text: str) -> str:
     return text
 
 
-def _split_message(content: str, max_len: int = 4000) -> list[str]:
-    """Split content into chunks within max_len, preferring line breaks."""
-    if len(content) <= max_len:
-        return [content]
-    chunks: list[str] = []
-    while content:
-        if len(content) <= max_len:
-            chunks.append(content)
-            break
-        cut = content[:max_len]
-        pos = cut.rfind('\n')
-        if pos == -1:
-            pos = cut.rfind(' ')
-        if pos == -1:
-            pos = max_len
-        chunks.append(content[:pos])
-        content = content[pos:].lstrip()
-    return chunks
-
-
 class TelegramChannel(BaseChannel):
     """
     Telegram channel using long polling.
@@ -107,6 +155,7 @@ class TelegramChannel(BaseChannel):
     """
 
     name = "telegram"
+    display_name = "Telegram"
 
     # Commands registered with Telegram's command menu
     BOT_COMMANDS = [
@@ -116,20 +165,36 @@ class TelegramChannel(BaseChannel):
         BotCommand("help", "Show available commands"),
     ]
 
-    def __init__(
+    def __init__(self, config: TelegramConfig, bus: MessageBus):
-        self,
-        config: TelegramConfig,
-        bus: MessageBus,
-        groq_api_key: str = "",
-    ):
         super().__init__(config, bus)
         self.config: TelegramConfig = config
-        self.groq_api_key = groq_api_key
         self._app: Application | None = None
         self._chat_ids: dict[str, int] = {}  # Map sender_id to chat_id for replies
         self._typing_tasks: dict[str, asyncio.Task] = {}  # chat_id -> typing loop task
         self._media_group_buffers: dict[str, dict] = {}
         self._media_group_tasks: dict[str, asyncio.Task] = {}
+        self._message_threads: dict[tuple[str, int], int] = {}
+        self._bot_user_id: int | None = None
+        self._bot_username: str | None = None
+
+    def is_allowed(self, sender_id: str) -> bool:
+        """Preserve Telegram's legacy id|username allowlist matching."""
+        if super().is_allowed(sender_id):
+            return True
+
+        allow_list = getattr(self.config, "allow_from", [])
+        if not allow_list or "*" in allow_list:
+            return False
+
+        sender_str = str(sender_id)
+        if sender_str.count("|") != 1:
+            return False
+
+        sid, username = sender_str.split("|", 1)
+        if not sid.isdigit() or not username:
+            return False
+
+        return sid in allow_list or username in allow_list
 
     async def start(self) -> None:
         """Start the Telegram bot with long polling."""
@@ -140,16 +205,21 @@ class TelegramChannel(BaseChannel):
         self._running = True
 
         # Build the application with larger connection pool to avoid pool-timeout on long runs
-        req = HTTPXRequest(connection_pool_size=16, pool_timeout=5.0, connect_timeout=30.0, read_timeout=30.0)
+        req = HTTPXRequest(
+            connection_pool_size=16,
+            pool_timeout=5.0,
+            connect_timeout=30.0,
+            read_timeout=30.0,
+            proxy=self.config.proxy if self.config.proxy else None,
+        )
         builder = Application.builder().token(self.config.token).request(req).get_updates_request(req)
-        if self.config.proxy:
-            builder = builder.proxy(self.config.proxy).get_updates_proxy(self.config.proxy)
         self._app = builder.build()
         self._app.add_error_handler(self._on_error)
 
         # Add command handlers
         self._app.add_handler(CommandHandler("start", self._on_start))
         self._app.add_handler(CommandHandler("new", self._forward_command))
+        self._app.add_handler(CommandHandler("stop", self._forward_command))
         self._app.add_handler(CommandHandler("help", self._on_help))
 
         # Add message handler for text, photos, voice, documents
@@ -169,6 +239,8 @@ class TelegramChannel(BaseChannel):
 
         # Get bot info and register command menu
         bot_info = await self._app.bot.get_me()
+        self._bot_user_id = getattr(bot_info, "id", None)
+        self._bot_username = getattr(bot_info, "username", None)
         logger.info("Telegram bot @{} connected", bot_info.username)
 
         try:
@@ -225,17 +297,25 @@ class TelegramChannel(BaseChannel):
             logger.warning("Telegram bot not running")
             return
 
-        self._stop_typing(msg.chat_id)
+        # Only stop typing indicator for final responses
+        if not msg.metadata.get("_progress", False):
+            self._stop_typing(msg.chat_id)
 
         try:
             chat_id = int(msg.chat_id)
         except ValueError:
             logger.error("Invalid chat_id: {}", msg.chat_id)
             return
+        reply_to_message_id = msg.metadata.get("message_id")
+        message_thread_id = msg.metadata.get("message_thread_id")
+        if message_thread_id is None and reply_to_message_id is not None:
+            message_thread_id = self._message_threads.get((msg.chat_id, reply_to_message_id))
+        thread_kwargs = {}
+        if message_thread_id is not None:
+            thread_kwargs["message_thread_id"] = message_thread_id
 
         reply_params = None
         if self.config.reply_to_message:
-            reply_to_message_id = msg.metadata.get("message_id")
             if reply_to_message_id:
                 reply_params = ReplyParameters(
                     message_id=reply_to_message_id,
@@ -256,7 +336,8 @@ class TelegramChannel(BaseChannel):
                     await sender(
                         chat_id=chat_id,
                         **{param: f},
-                        reply_parameters=reply_params
+                        reply_parameters=reply_params,
+                        **thread_kwargs,
                     )
             except Exception as e:
                 filename = media_path.rsplit("/", 1)[-1]
@@ -264,30 +345,71 @@ class TelegramChannel(BaseChannel):
                 await self._app.bot.send_message(
                     chat_id=chat_id,
                     text=f"[Failed to send: {filename}]",
-                    reply_parameters=reply_params
+                    reply_parameters=reply_params,
+                    **thread_kwargs,
                 )
 
         # Send text content
         if msg.content and msg.content != "[empty message]":
-            for chunk in _split_message(msg.content):
+            is_progress = msg.metadata.get("_progress", False)
-                try:
+
-                    html = _markdown_to_telegram_html(chunk)
+            for chunk in split_message(msg.content, TELEGRAM_MAX_MESSAGE_LEN):
-                    await self._app.bot.send_message(
+                # Final response: simulate streaming via draft, then persist
-                        chat_id=chat_id,
+                if not is_progress:
-                        text=html,
+                    await self._send_with_streaming(chat_id, chunk, reply_params, thread_kwargs)
-                        parse_mode="HTML",
+                else:
-                        reply_parameters=reply_params
+                    await self._send_text(chat_id, chunk, reply_params, thread_kwargs)
-                    )
+
-                except Exception as e:
+    async def _send_text(
-                    logger.warning("HTML parse failed, falling back to plain text: {}", e)
+        self,
-                    try:
+        chat_id: int,
-                        await self._app.bot.send_message(
+        text: str,
-                            chat_id=chat_id,
+        reply_params=None,
-                            text=chunk,
+        thread_kwargs: dict | None = None,
-                            reply_parameters=reply_params
+    ) -> None:
-                        )
+        """Send a plain text message with HTML fallback."""
-                    except Exception as e2:
+        try:
-                        logger.error("Error sending Telegram message: {}", e2)
+            html = _markdown_to_telegram_html(text)
+            await self._app.bot.send_message(
+                chat_id=chat_id, text=html, parse_mode="HTML",
+                reply_parameters=reply_params,
+                **(thread_kwargs or {}),
+            )
+        except Exception as e:
+            logger.warning("HTML parse failed, falling back to plain text: {}", e)
+            try:
+                await self._app.bot.send_message(
+                    chat_id=chat_id,
+                    text=text,
+                    reply_parameters=reply_params,
+                    **(thread_kwargs or {}),
+                )
+            except Exception as e2:
+                logger.error("Error sending Telegram message: {}", e2)
+
+    async def _send_with_streaming(
+        self,
+        chat_id: int,
+        text: str,
+        reply_params=None,
+        thread_kwargs: dict | None = None,
+    ) -> None:
+        """Simulate streaming via send_message_draft, then persist with send_message."""
+        draft_id = int(time.time() * 1000) % (2**31)
+        try:
+            step = max(len(text) // 8, 40)
+            for i in range(step, len(text), step):
+                await self._app.bot.send_message_draft(
+                    chat_id=chat_id, draft_id=draft_id, text=text[:i],
+                )
+                await asyncio.sleep(0.04)
+            await self._app.bot.send_message_draft(
+                chat_id=chat_id, draft_id=draft_id, text=text,
+            )
+            await asyncio.sleep(0.15)
+        except Exception:
+            pass
+        await self._send_text(chat_id, text, reply_params, thread_kwargs)
 
     async def _on_start(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
         """Handle /start command."""
@@ -318,14 +440,114 @@ class TelegramChannel(BaseChannel):
         sid = str(user.id)
         return f"{sid}|{user.username}" if user.username else sid
 
+    @staticmethod
+    def _derive_topic_session_key(message) -> str | None:
+        """Derive topic-scoped session key for non-private Telegram chats."""
+        message_thread_id = getattr(message, "message_thread_id", None)
+        if message.chat.type == "private" or message_thread_id is None:
+            return None
+        return f"telegram:{message.chat_id}:topic:{message_thread_id}"
+
+    @staticmethod
+    def _build_message_metadata(message, user) -> dict:
+        """Build common Telegram inbound metadata payload."""
+        return {
+            "message_id": message.message_id,
+            "user_id": user.id,
+            "username": user.username,
+            "first_name": user.first_name,
+            "is_group": message.chat.type != "private",
+            "message_thread_id": getattr(message, "message_thread_id", None),
+            "is_forum": bool(getattr(message.chat, "is_forum", False)),
+        }
+
+    async def _ensure_bot_identity(self) -> tuple[int | None, str | None]:
+        """Load bot identity once and reuse it for mention/reply checks."""
+        if self._bot_user_id is not None or self._bot_username is not None:
+            return self._bot_user_id, self._bot_username
+        if not self._app:
+            return None, None
+        bot_info = await self._app.bot.get_me()
+        self._bot_user_id = getattr(bot_info, "id", None)
+        self._bot_username = getattr(bot_info, "username", None)
+        return self._bot_user_id, self._bot_username
+
+    @staticmethod
+    def _has_mention_entity(
+        text: str,
+        entities,
+        bot_username: str,
+        bot_id: int | None,
+    ) -> bool:
+        """Check Telegram mention entities against the bot username."""
+        handle = f"@{bot_username}".lower()
+        for entity in entities or []:
+            entity_type = getattr(entity, "type", None)
+            if entity_type == "text_mention":
+                user = getattr(entity, "user", None)
+                if user is not None and bot_id is not None and getattr(user, "id", None) == bot_id:
+                    return True
+                continue
+            if entity_type != "mention":
+                continue
+            offset = getattr(entity, "offset", None)
+            length = getattr(entity, "length", None)
+            if offset is None or length is None:
+                continue
+            if text[offset : offset + length].lower() == handle:
+                return True
+        return handle in text.lower()
+
+    async def _is_group_message_for_bot(self, message) -> bool:
+        """Allow group messages when policy is open, @mentioned, or replying to the bot."""
+        if message.chat.type == "private" or self.config.group_policy == "open":
+            return True
+
+        bot_id, bot_username = await self._ensure_bot_identity()
+        if bot_username:
+            text = message.text or ""
+            caption = message.caption or ""
+            if self._has_mention_entity(
+                text,
+                getattr(message, "entities", None),
+                bot_username,
+                bot_id,
+            ):
+                return True
+            if self._has_mention_entity(
+                caption,
+                getattr(message, "caption_entities", None),
+                bot_username,
+                bot_id,
+            ):
+                return True
+
+        reply_user = getattr(getattr(message, "reply_to_message", None), "from_user", None)
+        return bool(bot_id and reply_user and reply_user.id == bot_id)
+
+    def _remember_thread_context(self, message) -> None:
+        """Cache topic thread id by chat/message id for follow-up replies."""
+        message_thread_id = getattr(message, "message_thread_id", None)
+        if message_thread_id is None:
+            return
+        key = (str(message.chat_id), message.message_id)
+        self._message_threads[key] = message_thread_id
+        if len(self._message_threads) > 1000:
+            self._message_threads.pop(next(iter(self._message_threads)))
+
     async def _forward_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
         """Forward slash commands to the bus for unified handling in AgentLoop."""
         if not update.message or not update.effective_user:
             return
+        message = update.message
+        user = update.effective_user
+        self._remember_thread_context(message)
         await self._handle_message(
-            sender_id=self._sender_id(update.effective_user),
+            sender_id=self._sender_id(user),
-            chat_id=str(update.message.chat_id),
+            chat_id=str(message.chat_id),
-            content=update.message.text,
+            content=message.text,
+            metadata=self._build_message_metadata(message, user),
+            session_key=self._derive_topic_session_key(message),
         )
 
     async def _on_message(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
@@ -337,10 +559,14 @@ class TelegramChannel(BaseChannel):
         user = update.effective_user
         chat_id = message.chat_id
         sender_id = self._sender_id(user)
+        self._remember_thread_context(message)
 
         # Store chat_id for replies
         self._chat_ids[sender_id] = chat_id
 
+        if not await self._is_group_message_for_bot(message):
+            return
+
         # Build content from text and/or media
         content_parts = []
         media_paths = []
@@ -372,23 +598,20 @@ class TelegramChannel(BaseChannel):
         if media_file and self._app:
             try:
                 file = await self._app.bot.get_file(media_file.file_id)
-                ext = self._get_extension(media_type, getattr(media_file, 'mime_type', None))
+                ext = self._get_extension(
-
+                    media_type,
-                # Save to workspace/media/
+                    getattr(media_file, 'mime_type', None),
-                from pathlib import Path
+                    getattr(media_file, 'file_name', None),
-                media_dir = Path.home() / ".nanobot" / "media"
+                )
-                media_dir.mkdir(parents=True, exist_ok=True)
+                media_dir = get_media_dir("telegram")
 
                 file_path = media_dir / f"{media_file.file_id[:16]}{ext}"
                 await file.download_to_drive(str(file_path))
 
                 media_paths.append(str(file_path))
 
-                # Handle voice transcription
+                if media_type in ("voice", "audio"):
-                if media_type == "voice" or media_type == "audio":
+                    transcription = await self.transcribe_audio(file_path)
-                    from nanobot.providers.transcription import GroqTranscriptionProvider
-                    transcriber = GroqTranscriptionProvider(api_key=self.groq_api_key)
-                    transcription = await transcriber.transcribe(file_path)
                     if transcription:
                         logger.info("Transcribed {}: {}...", media_type, transcription[:50])
                         content_parts.append(f"[transcription: {transcription}]")
@@ -407,6 +630,8 @@ class TelegramChannel(BaseChannel):
         logger.debug("Telegram message from {}: {}...", sender_id, content[:50])
 
         str_chat_id = str(chat_id)
+        metadata = self._build_message_metadata(message, user)
+        session_key = self._derive_topic_session_key(message)
 
         # Telegram media groups: buffer briefly, forward as one aggregated turn.
         if media_group_id := getattr(message, "media_group_id", None):
@@ -415,11 +640,8 @@ class TelegramChannel(BaseChannel):
                 self._media_group_buffers[key] = {
                     "sender_id": sender_id, "chat_id": str_chat_id,
                     "contents": [], "media": [],
-                    "metadata": {
+                    "metadata": metadata,
-                        "message_id": message.message_id, "user_id": user.id,
+                    "session_key": session_key,
-                        "username": user.username, "first_name": user.first_name,
-                        "is_group": message.chat.type != "private",
-                    },
                 }
                 self._start_typing(str_chat_id)
             buf = self._media_group_buffers[key]
@@ -439,13 +661,8 @@ class TelegramChannel(BaseChannel):
             chat_id=str_chat_id,
             content=content,
             media=media_paths,
-            metadata={
+            metadata=metadata,
-                "message_id": message.message_id,
+            session_key=session_key,
-                "user_id": user.id,
-                "username": user.username,
-                "first_name": user.first_name,
-                "is_group": message.chat.type != "private"
-            }
         )
 
     async def _flush_media_group(self, key: str) -> None:
@@ -459,6 +676,7 @@ class TelegramChannel(BaseChannel):
                 sender_id=buf["sender_id"], chat_id=buf["chat_id"],
                 content=content, media=list(dict.fromkeys(buf["media"])),
                 metadata=buf["metadata"],
+                session_key=buf.get("session_key"),
             )
         finally:
             self._media_group_tasks.pop(key, None)
@@ -490,8 +708,13 @@ class TelegramChannel(BaseChannel):
         """Log polling / handler errors instead of silently swallowing them."""
         logger.error("Telegram error: {}", context.error)
 
-    def _get_extension(self, media_type: str, mime_type: str | None) -> str:
+    def _get_extension(
-        """Get file extension based on media type."""
+        self,
+        media_type: str,
+        mime_type: str | None,
+        filename: str | None = None,
+    ) -> str:
+        """Get file extension based on media type or original filename."""
         if mime_type:
             ext_map = {
                 "image/jpeg": ".jpg", "image/png": ".png", "image/gif": ".gif",
@@ -501,4 +724,12 @@ class TelegramChannel(BaseChannel):
                 return ext_map[mime_type]
 
         type_map = {"image": ".jpg", "voice": ".ogg", "audio": ".mp3", "file": ""}
-        return type_map.get(media_type, "")
+        if ext := type_map.get(media_type, ""):
+            return ext
+
+        if filename:
+            from pathlib import Path
+
+            return "".join(Path(filename).suffixes)
+
+        return ""

nanobot/channels/wecom.py

@@ -0,0 +1,353 @@
+"""WeCom (Enterprise WeChat) channel implementation using wecom_aibot_sdk."""
+
+import asyncio
+import importlib.util
+import os
+from collections import OrderedDict
+from typing import Any
+
+from loguru import logger
+
+from nanobot.bus.events import OutboundMessage
+from nanobot.bus.queue import MessageBus
+from nanobot.channels.base import BaseChannel
+from nanobot.config.paths import get_media_dir
+from nanobot.config.schema import WecomConfig
+
+WECOM_AVAILABLE = importlib.util.find_spec("wecom_aibot_sdk") is not None
+
+# Message type display mapping
+MSG_TYPE_MAP = {
+    "image": "[image]",
+    "voice": "[voice]",
+    "file": "[file]",
+    "mixed": "[mixed content]",
+}
+
+
+class WecomChannel(BaseChannel):
+    """
+    WeCom (Enterprise WeChat) channel using WebSocket long connection.
+
+    Uses WebSocket to receive events - no public IP or webhook required.
+
+    Requires:
+    - Bot ID and Secret from WeCom AI Bot platform
+    """
+
+    name = "wecom"
+    display_name = "WeCom"
+
+    def __init__(self, config: WecomConfig, bus: MessageBus):
+        super().__init__(config, bus)
+        self.config: WecomConfig = config
+        self._client: Any = None
+        self._processed_message_ids: OrderedDict[str, None] = OrderedDict()
+        self._loop: asyncio.AbstractEventLoop | None = None
+        self._generate_req_id = None
+        # Store frame headers for each chat to enable replies
+        self._chat_frames: dict[str, Any] = {}
+
+    async def start(self) -> None:
+        """Start the WeCom bot with WebSocket long connection."""
+        if not WECOM_AVAILABLE:
+            logger.error("WeCom SDK not installed. Run: pip install nanobot-ai[wecom]")
+            return
+
+        if not self.config.bot_id or not self.config.secret:
+            logger.error("WeCom bot_id and secret not configured")
+            return
+
+        from wecom_aibot_sdk import WSClient, generate_req_id
+
+        self._running = True
+        self._loop = asyncio.get_running_loop()
+        self._generate_req_id = generate_req_id
+
+        # Create WebSocket client
+        self._client = WSClient({
+            "bot_id": self.config.bot_id,
+            "secret": self.config.secret,
+            "reconnect_interval": 1000,
+            "max_reconnect_attempts": -1,  # Infinite reconnect
+            "heartbeat_interval": 30000,
+        })
+
+        # Register event handlers
+        self._client.on("connected", self._on_connected)
+        self._client.on("authenticated", self._on_authenticated)
+        self._client.on("disconnected", self._on_disconnected)
+        self._client.on("error", self._on_error)
+        self._client.on("message.text", self._on_text_message)
+        self._client.on("message.image", self._on_image_message)
+        self._client.on("message.voice", self._on_voice_message)
+        self._client.on("message.file", self._on_file_message)
+        self._client.on("message.mixed", self._on_mixed_message)
+        self._client.on("event.enter_chat", self._on_enter_chat)
+
+        logger.info("WeCom bot starting with WebSocket long connection")
+        logger.info("No public IP required - using WebSocket to receive events")
+
+        # Connect
+        await self._client.connect_async()
+
+        # Keep running until stopped
+        while self._running:
+            await asyncio.sleep(1)
+
+    async def stop(self) -> None:
+        """Stop the WeCom bot."""
+        self._running = False
+        if self._client:
+            await self._client.disconnect()
+        logger.info("WeCom bot stopped")
+
+    async def _on_connected(self, frame: Any) -> None:
+        """Handle WebSocket connected event."""
+        logger.info("WeCom WebSocket connected")
+
+    async def _on_authenticated(self, frame: Any) -> None:
+        """Handle authentication success event."""
+        logger.info("WeCom authenticated successfully")
+
+    async def _on_disconnected(self, frame: Any) -> None:
+        """Handle WebSocket disconnected event."""
+        reason = frame.body if hasattr(frame, 'body') else str(frame)
+        logger.warning("WeCom WebSocket disconnected: {}", reason)
+
+    async def _on_error(self, frame: Any) -> None:
+        """Handle error event."""
+        logger.error("WeCom error: {}", frame)
+
+    async def _on_text_message(self, frame: Any) -> None:
+        """Handle text message."""
+        await self._process_message(frame, "text")
+
+    async def _on_image_message(self, frame: Any) -> None:
+        """Handle image message."""
+        await self._process_message(frame, "image")
+
+    async def _on_voice_message(self, frame: Any) -> None:
+        """Handle voice message."""
+        await self._process_message(frame, "voice")
+
+    async def _on_file_message(self, frame: Any) -> None:
+        """Handle file message."""
+        await self._process_message(frame, "file")
+
+    async def _on_mixed_message(self, frame: Any) -> None:
+        """Handle mixed content message."""
+        await self._process_message(frame, "mixed")
+
+    async def _on_enter_chat(self, frame: Any) -> None:
+        """Handle enter_chat event (user opens chat with bot)."""
+        try:
+            # Extract body from WsFrame dataclass or dict
+            if hasattr(frame, 'body'):
+                body = frame.body or {}
+            elif isinstance(frame, dict):
+                body = frame.get("body", frame)
+            else:
+                body = {}
+
+            chat_id = body.get("chatid", "") if isinstance(body, dict) else ""
+
+            if chat_id and self.config.welcome_message:
+                await self._client.reply_welcome(frame, {
+                    "msgtype": "text",
+                    "text": {"content": self.config.welcome_message},
+                })
+        except Exception as e:
+            logger.error("Error handling enter_chat: {}", e)
+
+    async def _process_message(self, frame: Any, msg_type: str) -> None:
+        """Process incoming message and forward to bus."""
+        try:
+            # Extract body from WsFrame dataclass or dict
+            if hasattr(frame, 'body'):
+                body = frame.body or {}
+            elif isinstance(frame, dict):
+                body = frame.get("body", frame)
+            else:
+                body = {}
+
+            # Ensure body is a dict
+            if not isinstance(body, dict):
+                logger.warning("Invalid body type: {}", type(body))
+                return
+
+            # Extract message info
+            msg_id = body.get("msgid", "")
+            if not msg_id:
+                msg_id = f"{body.get('chatid', '')}_{body.get('sendertime', '')}"
+
+            # Deduplication check
+            if msg_id in self._processed_message_ids:
+                return
+            self._processed_message_ids[msg_id] = None
+
+            # Trim cache
+            while len(self._processed_message_ids) > 1000:
+                self._processed_message_ids.popitem(last=False)
+
+            # Extract sender info from "from" field (SDK format)
+            from_info = body.get("from", {})
+            sender_id = from_info.get("userid", "unknown") if isinstance(from_info, dict) else "unknown"
+
+            # For single chat, chatid is the sender's userid
+            # For group chat, chatid is provided in body
+            chat_type = body.get("chattype", "single")
+            chat_id = body.get("chatid", sender_id)
+
+            content_parts = []
+
+            if msg_type == "text":
+                text = body.get("text", {}).get("content", "")
+                if text:
+                    content_parts.append(text)
+
+            elif msg_type == "image":
+                image_info = body.get("image", {})
+                file_url = image_info.get("url", "")
+                aes_key = image_info.get("aeskey", "")
+
+                if file_url and aes_key:
+                    file_path = await self._download_and_save_media(file_url, aes_key, "image")
+                    if file_path:
+                        filename = os.path.basename(file_path)
+                        content_parts.append(f"[image: {filename}]\n[Image: source: {file_path}]")
+                    else:
+                        content_parts.append("[image: download failed]")
+                else:
+                    content_parts.append("[image: download failed]")
+
+            elif msg_type == "voice":
+                voice_info = body.get("voice", {})
+                # Voice message already contains transcribed content from WeCom
+                voice_content = voice_info.get("content", "")
+                if voice_content:
+                    content_parts.append(f"[voice] {voice_content}")
+                else:
+                    content_parts.append("[voice]")
+
+            elif msg_type == "file":
+                file_info = body.get("file", {})
+                file_url = file_info.get("url", "")
+                aes_key = file_info.get("aeskey", "")
+                file_name = file_info.get("name", "unknown")
+
+                if file_url and aes_key:
+                    file_path = await self._download_and_save_media(file_url, aes_key, "file", file_name)
+                    if file_path:
+                        content_parts.append(f"[file: {file_name}]\n[File: source: {file_path}]")
+                    else:
+                        content_parts.append(f"[file: {file_name}: download failed]")
+                else:
+                    content_parts.append(f"[file: {file_name}: download failed]")
+
+            elif msg_type == "mixed":
+                # Mixed content contains multiple message items
+                msg_items = body.get("mixed", {}).get("item", [])
+                for item in msg_items:
+                    item_type = item.get("type", "")
+                    if item_type == "text":
+                        text = item.get("text", {}).get("content", "")
+                        if text:
+                            content_parts.append(text)
+                    else:
+                        content_parts.append(MSG_TYPE_MAP.get(item_type, f"[{item_type}]"))
+
+            else:
+                content_parts.append(MSG_TYPE_MAP.get(msg_type, f"[{msg_type}]"))
+
+            content = "\n".join(content_parts) if content_parts else ""
+
+            if not content:
+                return
+
+            # Store frame for this chat to enable replies
+            self._chat_frames[chat_id] = frame
+
+            # Forward to message bus
+            # Note: media paths are included in content for broader model compatibility
+            await self._handle_message(
+                sender_id=sender_id,
+                chat_id=chat_id,
+                content=content,
+                media=None,
+                metadata={
+                    "message_id": msg_id,
+                    "msg_type": msg_type,
+                    "chat_type": chat_type,
+                }
+            )
+
+        except Exception as e:
+            logger.error("Error processing WeCom message: {}", e)
+
+    async def _download_and_save_media(
+        self,
+        file_url: str,
+        aes_key: str,
+        media_type: str,
+        filename: str | None = None,
+    ) -> str | None:
+        """
+        Download and decrypt media from WeCom.
+
+        Returns:
+            file_path or None if download failed
+        """
+        try:
+            data, fname = await self._client.download_file(file_url, aes_key)
+
+            if not data:
+                logger.warning("Failed to download media from WeCom")
+                return None
+
+            media_dir = get_media_dir("wecom")
+            if not filename:
+                filename = fname or f"{media_type}_{hash(file_url) % 100000}"
+            filename = os.path.basename(filename)
+
+            file_path = media_dir / filename
+            file_path.write_bytes(data)
+            logger.debug("Downloaded {} to {}", media_type, file_path)
+            return str(file_path)
+
+        except Exception as e:
+            logger.error("Error downloading media: {}", e)
+            return None
+
+    async def send(self, msg: OutboundMessage) -> None:
+        """Send a message through WeCom."""
+        if not self._client:
+            logger.warning("WeCom client not initialized")
+            return
+
+        try:
+            content = msg.content.strip()
+            if not content:
+                return
+
+            # Get the stored frame for this chat
+            frame = self._chat_frames.get(msg.chat_id)
+            if not frame:
+                logger.warning("No frame found for chat {}, cannot reply", msg.chat_id)
+                return
+
+            # Use streaming reply for better UX
+            stream_id = self._generate_req_id("stream")
+
+            # Send as streaming message with finish=True
+            await self._client.reply_stream(
+                frame,
+                stream_id,
+                content,
+                finish=True,
+            )
+
+            logger.debug("WeCom message sent to {}", msg.chat_id)
+
+        except Exception as e:
+            logger.error("Error sending WeCom message: {}", e)

nanobot/channels/whatsapp.py

@@ -2,6 +2,7 @@
 
 import asyncio
 import json
+import mimetypes
 from collections import OrderedDict
 
 from loguru import logger
@@ -21,6 +22,7 @@ class WhatsAppChannel(BaseChannel):
     """
 
     name = "whatsapp"
+    display_name = "WhatsApp"
 
     def __init__(self, config: WhatsAppConfig, bus: MessageBus):
         super().__init__(config, bus)
@@ -128,10 +130,22 @@ class WhatsAppChannel(BaseChannel):
                 logger.info("Voice message received from {}, but direct download from bridge is not yet supported.", sender_id)
                 content = "[Voice Message: Transcription not available for WhatsApp yet]"
 
+            # Extract media paths (images/documents/videos downloaded by the bridge)
+            media_paths = data.get("media") or []
+
+            # Build content tags matching Telegram's pattern: [image: /path] or [file: /path]
+            if media_paths:
+                for p in media_paths:
+                    mime, _ = mimetypes.guess_type(p)
+                    media_type = "image" if mime and mime.startswith("image/") else "file"
+                    media_tag = f"[{media_type}: {p}]"
+                    content = f"{content}\n{media_tag}" if content else media_tag
+
             await self._handle_message(
                 sender_id=sender_id,
                 chat_id=sender,  # Use full LID for replies
                 content=content,
+                media=media_paths,
                 metadata={
                     "message_id": message_id,
                     "timestamp": data.get("timestamp"),

nanobot/cli/commands.py

@@ -7,6 +7,17 @@ import signal
 import sys
 from pathlib import Path
 
+# Force UTF-8 encoding for Windows console
+if sys.platform == "win32":
+    if sys.stdout.encoding != "utf-8":
+        os.environ["PYTHONIOENCODING"] = "utf-8"
+        # Re-open stdout/stderr with UTF-8 encoding
+        try:
+            sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+            sys.stderr.reconfigure(encoding="utf-8", errors="replace")
+        except Exception:
+            pass
+
 import typer
 from prompt_toolkit import PromptSession
 from prompt_toolkit.formatted_text import HTML
@@ -18,6 +29,7 @@ from rich.table import Table
 from rich.text import Text
 
 from nanobot import __logo__, __version__
+from nanobot.config.paths import get_workspace_path
 from nanobot.config.schema import Config
 from nanobot.utils.helpers import sync_workspace_templates
 
@@ -87,7 +99,9 @@ def _init_prompt_session() -> None:
     except Exception:
         pass
 
-    history_file = Path.home() / ".nanobot" / "history" / "cli_history"
+    from nanobot.config.paths import get_cli_history_path
+
+    history_file = get_cli_history_path()
     history_file.parent.mkdir(parents=True, exist_ok=True)
 
     _PROMPT_SESSION = PromptSession(
@@ -158,7 +172,6 @@ def onboard():
     """Initialize nanobot configuration and workspace."""
     from nanobot.config.loader import get_config_path, load_config, save_config
     from nanobot.config.schema import Config
-    from nanobot.utils.helpers import get_workspace_path
 
     config_path = get_config_path()
 
@@ -178,6 +191,8 @@ def onboard():
         save_config(Config())
         console.print(f"[green]✓[/green] Created config at {config_path}")
 
+    console.print("[dim]Config template now uses `maxTokens` + `contextWindowTokens`; `memoryWindow` is no longer a runtime setting.[/dim]")
+
     # Create workspace
     workspace = get_workspace_path()
 
@@ -200,9 +215,9 @@ def onboard():
 
 def _make_provider(config: Config):
     """Create the appropriate LLM provider from config."""
-    from nanobot.providers.custom_provider import CustomProvider
+    from nanobot.providers.base import GenerationSettings
-    from nanobot.providers.litellm_provider import LiteLLMProvider
     from nanobot.providers.openai_codex_provider import OpenAICodexProvider
+    from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
 
     model = config.agents.defaults.model
     provider_name = config.get_provider_name(model)
@@ -210,30 +225,79 @@ def _make_provider(config: Config):
 
     # OpenAI Codex (OAuth)
     if provider_name == "openai_codex" or model.startswith("openai-codex/"):
-        return OpenAICodexProvider(default_model=model)
+        provider = OpenAICodexProvider(default_model=model)
-
     # Custom: direct OpenAI-compatible endpoint, bypasses LiteLLM
-    if provider_name == "custom":
+    elif provider_name == "custom":
-        return CustomProvider(
+        from nanobot.providers.custom_provider import CustomProvider
+        provider = CustomProvider(
             api_key=p.api_key if p else "no-key",
             api_base=config.get_api_base(model) or "http://localhost:8000/v1",
             default_model=model,
         )
+    # Azure OpenAI: direct Azure OpenAI endpoint with deployment name
+    elif provider_name == "azure_openai":
+        if not p or not p.api_key or not p.api_base:
+            console.print("[red]Error: Azure OpenAI requires api_key and api_base.[/red]")
+            console.print("Set them in ~/.nanobot/config.json under providers.azure_openai section")
+            console.print("Use the model field to specify the deployment name.")
+            raise typer.Exit(1)
+        provider = AzureOpenAIProvider(
+            api_key=p.api_key,
+            api_base=p.api_base,
+            default_model=model,
+        )
+    else:
+        from nanobot.providers.litellm_provider import LiteLLMProvider
+        from nanobot.providers.registry import find_by_name
+        spec = find_by_name(provider_name)
+        if not model.startswith("bedrock/") and not (p and p.api_key) and not (spec and (spec.is_oauth or spec.is_local)):
+            console.print("[red]Error: No API key configured.[/red]")
+            console.print("Set one in ~/.nanobot/config.json under providers section")
+            raise typer.Exit(1)
+        provider = LiteLLMProvider(
+            api_key=p.api_key if p else None,
+            api_base=config.get_api_base(model),
+            default_model=model,
+            extra_headers=p.extra_headers if p else None,
+            provider_name=provider_name,
+        )
 
-    from nanobot.providers.registry import find_by_name
+    defaults = config.agents.defaults
-    spec = find_by_name(provider_name)
+    provider.generation = GenerationSettings(
-    if not model.startswith("bedrock/") and not (p and p.api_key) and not (spec and spec.is_oauth):
+        temperature=defaults.temperature,
-        console.print("[red]Error: No API key configured.[/red]")
+        max_tokens=defaults.max_tokens,
-        console.print("Set one in ~/.nanobot/config.json under providers section")
+        reasoning_effort=defaults.reasoning_effort,
-        raise typer.Exit(1)
-
-    return LiteLLMProvider(
-        api_key=p.api_key if p else None,
-        api_base=config.get_api_base(model),
-        default_model=model,
-        extra_headers=p.extra_headers if p else None,
-        provider_name=provider_name,
     )
+    return provider
+
+
+def _load_runtime_config(config: str | None = None, workspace: str | None = None) -> Config:
+    """Load config and optionally override the active workspace."""
+    from nanobot.config.loader import load_config, set_config_path
+
+    config_path = None
+    if config:
+        config_path = Path(config).expanduser().resolve()
+        if not config_path.exists():
+            console.print(f"[red]Error: Config file not found: {config_path}[/red]")
+            raise typer.Exit(1)
+        set_config_path(config_path)
+        console.print(f"[dim]Using config: {config_path}[/dim]")
+
+    loaded = load_config(config_path)
+    if workspace:
+        loaded.agents.defaults.workspace = workspace
+    return loaded
+
+
+def _print_deprecated_memory_window_notice(config: Config) -> None:
+    """Warn when running with old memoryWindow-only config."""
+    if config.agents.defaults.should_warn_deprecated_memory_window:
+        console.print(
+            "[yellow]Hint:[/yellow] Detected deprecated `memoryWindow` without "
+            "`contextWindowTokens`. `memoryWindow` is ignored; run "
+            "[cyan]nanobot onboard[/cyan] to refresh your config template."
+        )
 
 
 # ============================================================================
@@ -243,14 +307,16 @@ def _make_provider(config: Config):
 
 @app.command()
 def gateway(
-    port: int = typer.Option(18790, "--port", "-p", help="Gateway port"),
+    port: int | None = typer.Option(None, "--port", "-p", help="Gateway port"),
+    workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
     verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
+    config: str | None = typer.Option(None, "--config", "-c", help="Path to config file"),
 ):
     """Start the nanobot gateway."""
     from nanobot.agent.loop import AgentLoop
     from nanobot.bus.queue import MessageBus
     from nanobot.channels.manager import ChannelManager
-    from nanobot.config.loader import get_data_dir, load_config
+    from nanobot.config.paths import get_cron_dir
     from nanobot.cron.service import CronService
     from nanobot.cron.types import CronJob
     from nanobot.heartbeat.service import HeartbeatService
@@ -260,16 +326,18 @@ def gateway(
         import logging
         logging.basicConfig(level=logging.DEBUG)
 
-    console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
+    config = _load_runtime_config(config, workspace)
+    _print_deprecated_memory_window_notice(config)
+    port = port if port is not None else config.gateway.port
 
-    config = load_config()
+    console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
     sync_workspace_templates(config.workspace_path)
     bus = MessageBus()
     provider = _make_provider(config)
     session_manager = SessionManager(config.workspace_path)
 
     # Create cron service first (callback set after agent creation)
-    cron_store_path = get_data_dir() / "cron" / "jobs.json"
+    cron_store_path = get_cron_dir() / "jobs.json"
     cron = CronService(cron_store_path)
 
     # Create agent with cron service
@@ -278,11 +346,8 @@ def gateway(
         provider=provider,
         workspace=config.workspace_path,
         model=config.agents.defaults.model,
-        temperature=config.agents.defaults.temperature,
-        max_tokens=config.agents.defaults.max_tokens,
         max_iterations=config.agents.defaults.max_tool_iterations,
-        memory_window=config.agents.defaults.memory_window,
+        context_window_tokens=config.agents.defaults.context_window_tokens,
-        reasoning_effort=config.agents.defaults.reasoning_effort,
         brave_api_key=config.tools.web.search.api_key or None,
         web_proxy=config.tools.web.proxy or None,
         exec_config=config.tools.exec,
@@ -296,6 +361,7 @@ def gateway(
     # Set cron callback (needs agent)
     async def on_cron_job(job: CronJob) -> str | None:
         """Execute a cron job through the agent."""
+        from nanobot.agent.tools.cron import CronTool
         from nanobot.agent.tools.message import MessageTool
         reminder_note = (
             "[Scheduled Task] Timer finished.\n\n"
@@ -303,12 +369,21 @@ def gateway(
             f"Scheduled instruction: {job.payload.message}"
         )
 
-        response = await agent.process_direct(
+        # Prevent the agent from scheduling new cron jobs during execution
-            reminder_note,
+        cron_tool = agent.tools.get("cron")
-            session_key=f"cron:{job.id}",
+        cron_token = None
-            channel=job.payload.channel or "cli",
+        if isinstance(cron_tool, CronTool):
-            chat_id=job.payload.to or "direct",
+            cron_token = cron_tool.set_cron_context(True)
-        )
+        try:
+            response = await agent.process_direct(
+                reminder_note,
+                session_key=f"cron:{job.id}",
+                channel=job.payload.channel or "cli",
+                chat_id=job.payload.to or "direct",
+            )
+        finally:
+            if isinstance(cron_tool, CronTool) and cron_token is not None:
+                cron_tool.reset_cron_context(cron_token)
 
         message_tool = agent.tools.get("message")
         if isinstance(message_tool, MessageTool) and message_tool._sent_in_turn:
@@ -420,6 +495,8 @@ def gateway(
 def agent(
     message: str = typer.Option(None, "--message", "-m", help="Message to send to the agent"),
     session_id: str = typer.Option("cli:direct", "--session", "-s", help="Session ID"),
+    workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
+    config: str | None = typer.Option(None, "--config", "-c", help="Config file path"),
     markdown: bool = typer.Option(True, "--markdown/--no-markdown", help="Render assistant output as Markdown"),
     logs: bool = typer.Option(False, "--logs/--no-logs", help="Show nanobot runtime logs during chat"),
 ):
@@ -428,17 +505,18 @@ def agent(
 
     from nanobot.agent.loop import AgentLoop
     from nanobot.bus.queue import MessageBus
-    from nanobot.config.loader import get_data_dir, load_config
+    from nanobot.config.paths import get_cron_dir
     from nanobot.cron.service import CronService
 
-    config = load_config()
+    config = _load_runtime_config(config, workspace)
+    _print_deprecated_memory_window_notice(config)
     sync_workspace_templates(config.workspace_path)
 
     bus = MessageBus()
     provider = _make_provider(config)
 
     # Create cron service for tool usage (no callback needed for CLI unless running)
-    cron_store_path = get_data_dir() / "cron" / "jobs.json"
+    cron_store_path = get_cron_dir() / "jobs.json"
     cron = CronService(cron_store_path)
 
     if logs:
@@ -451,11 +529,8 @@ def agent(
         provider=provider,
         workspace=config.workspace_path,
         model=config.agents.defaults.model,
-        temperature=config.agents.defaults.temperature,
-        max_tokens=config.agents.defaults.max_tokens,
         max_iterations=config.agents.defaults.max_tool_iterations,
-        memory_window=config.agents.defaults.memory_window,
+        context_window_tokens=config.agents.defaults.context_window_tokens,
-        reasoning_effort=config.agents.defaults.reasoning_effort,
         brave_api_key=config.tools.web.search.api_key or None,
         web_proxy=config.tools.web.proxy or None,
         exec_config=config.tools.exec,
@@ -501,12 +576,21 @@ def agent(
         else:
             cli_channel, cli_chat_id = "cli", session_id
 
-        def _exit_on_sigint(signum, frame):
+        def _handle_signal(signum, frame):
+            sig_name = signal.Signals(signum).name
             _restore_terminal()
-            console.print("\nGoodbye!")
+            console.print(f"\nReceived {sig_name}, goodbye!")
-            os._exit(0)
+            sys.exit(0)
 
-        signal.signal(signal.SIGINT, _exit_on_sigint)
+        signal.signal(signal.SIGINT, _handle_signal)
+        signal.signal(signal.SIGTERM, _handle_signal)
+        # SIGHUP is not available on Windows
+        if hasattr(signal, 'SIGHUP'):
+            signal.signal(signal.SIGHUP, _handle_signal)
+        # Ignore SIGPIPE to prevent silent process termination when writing to closed pipes
+        # SIGPIPE is not available on Windows
+        if hasattr(signal, 'SIGPIPE'):
+            signal.signal(signal.SIGPIPE, signal.SIG_IGN)
 
         async def run_interactive():
             bus_task = asyncio.create_task(agent_loop.run())
@@ -599,6 +683,7 @@ app.add_typer(channels_app, name="channels")
 @channels_app.command("status")
 def channels_status():
     """Show channel status."""
+    from nanobot.channels.registry import discover_channel_names, load_channel_class
     from nanobot.config.loader import load_config
 
     config = load_config()
@@ -606,85 +691,19 @@ def channels_status():
     table = Table(title="Channel Status")
     table.add_column("Channel", style="cyan")
     table.add_column("Enabled", style="green")
-    table.add_column("Configuration", style="yellow")
 
-    # WhatsApp
+    for modname in sorted(discover_channel_names()):
-    wa = config.channels.whatsapp
+        section = getattr(config.channels, modname, None)
-    table.add_row(
+        enabled = section and getattr(section, "enabled", False)
-        "WhatsApp",
+        try:
-        "✓" if wa.enabled else "✗",
+            cls = load_channel_class(modname)
-        wa.bridge_url
+            display = cls.display_name
-    )
+        except ImportError:
-
+            display = modname.title()
-    dc = config.channels.discord
+        table.add_row(
-    table.add_row(
+            display,
-        "Discord",
+            "[green]\u2713[/green]" if enabled else "[dim]\u2717[/dim]",
-        "✓" if dc.enabled else "✗",
+        )
-        dc.gateway_url
-    )
-
-    # Feishu
-    fs = config.channels.feishu
-    fs_config = f"app_id: {fs.app_id[:10]}..." if fs.app_id else "[dim]not configured[/dim]"
-    table.add_row(
-        "Feishu",
-        "✓" if fs.enabled else "✗",
-        fs_config
-    )
-
-    # Mochat
-    mc = config.channels.mochat
-    mc_base = mc.base_url or "[dim]not configured[/dim]"
-    table.add_row(
-        "Mochat",
-        "✓" if mc.enabled else "✗",
-        mc_base
-    )
-
-    # Telegram
-    tg = config.channels.telegram
-    tg_config = f"token: {tg.token[:10]}..." if tg.token else "[dim]not configured[/dim]"
-    table.add_row(
-        "Telegram",
-        "✓" if tg.enabled else "✗",
-        tg_config
-    )
-
-    # Slack
-    slack = config.channels.slack
-    slack_config = "socket" if slack.app_token and slack.bot_token else "[dim]not configured[/dim]"
-    table.add_row(
-        "Slack",
-        "✓" if slack.enabled else "✗",
-        slack_config
-    )
-
-    # DingTalk
-    dt = config.channels.dingtalk
-    dt_config = f"client_id: {dt.client_id[:10]}..." if dt.client_id else "[dim]not configured[/dim]"
-    table.add_row(
-        "DingTalk",
-        "✓" if dt.enabled else "✗",
-        dt_config
-    )
-
-    # QQ
-    qq = config.channels.qq
-    qq_config = f"app_id: {qq.app_id[:10]}..." if qq.app_id else "[dim]not configured[/dim]"
-    table.add_row(
-        "QQ",
-        "✓" if qq.enabled else "✗",
-        qq_config
-    )
-
-    # Email
-    em = config.channels.email
-    em_config = em.imap_host if em.imap_host else "[dim]not configured[/dim]"
-    table.add_row(
-        "Email",
-        "✓" if em.enabled else "✗",
-        em_config
-    )
 
     console.print(table)
 
@@ -695,7 +714,9 @@ def _get_bridge_dir() -> Path:
     import subprocess
 
     # User's bridge location
-    user_bridge = Path.home() / ".nanobot" / "bridge"
+    from nanobot.config.paths import get_bridge_install_dir
+
+    user_bridge = get_bridge_install_dir()
 
     # Check if already built
     if (user_bridge / "dist" / "index.js").exists():
@@ -753,6 +774,7 @@ def channels_login():
     import subprocess
 
     from nanobot.config.loader import load_config
+    from nanobot.config.paths import get_runtime_subdir
 
     config = load_config()
     bridge_dir = _get_bridge_dir()
@@ -763,6 +785,7 @@ def channels_login():
     env = {**os.environ}
     if config.channels.whatsapp.bridge_token:
         env["BRIDGE_TOKEN"] = config.channels.whatsapp.bridge_token
+    env["AUTH_DIR"] = str(get_runtime_subdir("whatsapp-auth"))
 
     try:
         subprocess.run(["npm", "start"], cwd=bridge_dir, check=True, env=env)
@@ -772,221 +795,6 @@ def channels_login():
         console.print("[red]npm not found. Please install Node.js.[/red]")
 
 
-# ============================================================================
-# Cron Commands
-# ============================================================================
-
-cron_app = typer.Typer(help="Manage scheduled tasks")
-app.add_typer(cron_app, name="cron")
-
-
-@cron_app.command("list")
-def cron_list(
-    all: bool = typer.Option(False, "--all", "-a", help="Include disabled jobs"),
-):
-    """List scheduled jobs."""
-    from nanobot.config.loader import get_data_dir
-    from nanobot.cron.service import CronService
-
-    store_path = get_data_dir() / "cron" / "jobs.json"
-    service = CronService(store_path)
-
-    jobs = service.list_jobs(include_disabled=all)
-
-    if not jobs:
-        console.print("No scheduled jobs.")
-        return
-
-    table = Table(title="Scheduled Jobs")
-    table.add_column("ID", style="cyan")
-    table.add_column("Name")
-    table.add_column("Schedule")
-    table.add_column("Status")
-    table.add_column("Next Run")
-
-    import time
-    from datetime import datetime as _dt
-    from zoneinfo import ZoneInfo
-    for job in jobs:
-        # Format schedule
-        if job.schedule.kind == "every":
-            sched = f"every {(job.schedule.every_ms or 0) // 1000}s"
-        elif job.schedule.kind == "cron":
-            sched = f"{job.schedule.expr or ''} ({job.schedule.tz})" if job.schedule.tz else (job.schedule.expr or "")
-        else:
-            sched = "one-time"
-
-        # Format next run
-        next_run = ""
-        if job.state.next_run_at_ms:
-            ts = job.state.next_run_at_ms / 1000
-            try:
-                tz = ZoneInfo(job.schedule.tz) if job.schedule.tz else None
-                next_run = _dt.fromtimestamp(ts, tz).strftime("%Y-%m-%d %H:%M")
-            except Exception:
-                next_run = time.strftime("%Y-%m-%d %H:%M", time.localtime(ts))
-
-        status = "[green]enabled[/green]" if job.enabled else "[dim]disabled[/dim]"
-
-        table.add_row(job.id, job.name, sched, status, next_run)
-
-    console.print(table)
-
-
-@cron_app.command("add")
-def cron_add(
-    name: str = typer.Option(..., "--name", "-n", help="Job name"),
-    message: str = typer.Option(..., "--message", "-m", help="Message for agent"),
-    every: int = typer.Option(None, "--every", "-e", help="Run every N seconds"),
-    cron_expr: str = typer.Option(None, "--cron", "-c", help="Cron expression (e.g. '0 9 * * *')"),
-    tz: str | None = typer.Option(None, "--tz", help="IANA timezone for cron (e.g. 'America/Vancouver')"),
-    at: str = typer.Option(None, "--at", help="Run once at time (ISO format)"),
-    deliver: bool = typer.Option(False, "--deliver", "-d", help="Deliver response to channel"),
-    to: str = typer.Option(None, "--to", help="Recipient for delivery"),
-    channel: str = typer.Option(None, "--channel", help="Channel for delivery (e.g. 'telegram', 'whatsapp')"),
-):
-    """Add a scheduled job."""
-    from nanobot.config.loader import get_data_dir
-    from nanobot.cron.service import CronService
-    from nanobot.cron.types import CronSchedule
-
-    if tz and not cron_expr:
-        console.print("[red]Error: --tz can only be used with --cron[/red]")
-        raise typer.Exit(1)
-
-    # Determine schedule type
-    if every:
-        schedule = CronSchedule(kind="every", every_ms=every * 1000)
-    elif cron_expr:
-        schedule = CronSchedule(kind="cron", expr=cron_expr, tz=tz)
-    elif at:
-        import datetime
-        dt = datetime.datetime.fromisoformat(at)
-        schedule = CronSchedule(kind="at", at_ms=int(dt.timestamp() * 1000))
-    else:
-        console.print("[red]Error: Must specify --every, --cron, or --at[/red]")
-        raise typer.Exit(1)
-
-    store_path = get_data_dir() / "cron" / "jobs.json"
-    service = CronService(store_path)
-
-    try:
-        job = service.add_job(
-            name=name,
-            schedule=schedule,
-            message=message,
-            deliver=deliver,
-            to=to,
-            channel=channel,
-        )
-    except ValueError as e:
-        console.print(f"[red]Error: {e}[/red]")
-        raise typer.Exit(1) from e
-
-    console.print(f"[green]✓[/green] Added job '{job.name}' ({job.id})")
-
-
-@cron_app.command("remove")
-def cron_remove(
-    job_id: str = typer.Argument(..., help="Job ID to remove"),
-):
-    """Remove a scheduled job."""
-    from nanobot.config.loader import get_data_dir
-    from nanobot.cron.service import CronService
-
-    store_path = get_data_dir() / "cron" / "jobs.json"
-    service = CronService(store_path)
-
-    if service.remove_job(job_id):
-        console.print(f"[green]✓[/green] Removed job {job_id}")
-    else:
-        console.print(f"[red]Job {job_id} not found[/red]")
-
-
-@cron_app.command("enable")
-def cron_enable(
-    job_id: str = typer.Argument(..., help="Job ID"),
-    disable: bool = typer.Option(False, "--disable", help="Disable instead of enable"),
-):
-    """Enable or disable a job."""
-    from nanobot.config.loader import get_data_dir
-    from nanobot.cron.service import CronService
-
-    store_path = get_data_dir() / "cron" / "jobs.json"
-    service = CronService(store_path)
-
-    job = service.enable_job(job_id, enabled=not disable)
-    if job:
-        status = "disabled" if disable else "enabled"
-        console.print(f"[green]✓[/green] Job '{job.name}' {status}")
-    else:
-        console.print(f"[red]Job {job_id} not found[/red]")
-
-
-@cron_app.command("run")
-def cron_run(
-    job_id: str = typer.Argument(..., help="Job ID to run"),
-    force: bool = typer.Option(False, "--force", "-f", help="Run even if disabled"),
-):
-    """Manually run a job."""
-    from loguru import logger
-
-    from nanobot.agent.loop import AgentLoop
-    from nanobot.bus.queue import MessageBus
-    from nanobot.config.loader import get_data_dir, load_config
-    from nanobot.cron.service import CronService
-    from nanobot.cron.types import CronJob
-    logger.disable("nanobot")
-
-    config = load_config()
-    provider = _make_provider(config)
-    bus = MessageBus()
-    agent_loop = AgentLoop(
-        bus=bus,
-        provider=provider,
-        workspace=config.workspace_path,
-        model=config.agents.defaults.model,
-        temperature=config.agents.defaults.temperature,
-        max_tokens=config.agents.defaults.max_tokens,
-        max_iterations=config.agents.defaults.max_tool_iterations,
-        memory_window=config.agents.defaults.memory_window,
-        reasoning_effort=config.agents.defaults.reasoning_effort,
-        brave_api_key=config.tools.web.search.api_key or None,
-        web_proxy=config.tools.web.proxy or None,
-        exec_config=config.tools.exec,
-        restrict_to_workspace=config.tools.restrict_to_workspace,
-        mcp_servers=config.tools.mcp_servers,
-        channels_config=config.channels,
-    )
-
-    store_path = get_data_dir() / "cron" / "jobs.json"
-    service = CronService(store_path)
-
-    result_holder = []
-
-    async def on_job(job: CronJob) -> str | None:
-        response = await agent_loop.process_direct(
-            job.payload.message,
-            session_key=f"cron:{job.id}",
-            channel=job.payload.channel or "cli",
-            chat_id=job.payload.to or "direct",
-        )
-        result_holder.append(response)
-        return response
-
-    service.on_job = on_job
-
-    async def run():
-        return await service.run_job(job_id, force=force)
-
-    if asyncio.run(run()):
-        console.print("[green]✓[/green] Job executed")
-        if result_holder:
-            _print_agent_response(result_holder[0], render_markdown=True)
-    else:
-        console.print(f"[red]Failed to run job {job_id}[/red]")
-
-
 # ============================================================================
 # Status Commands
 # ============================================================================

nanobot/config/__init__.py

@@ -1,6 +1,30 @@
 """Configuration module for nanobot."""
 
 from nanobot.config.loader import get_config_path, load_config
+from nanobot.config.paths import (
+    get_bridge_install_dir,
+    get_cli_history_path,
+    get_cron_dir,
+    get_data_dir,
+    get_legacy_sessions_dir,
+    get_logs_dir,
+    get_media_dir,
+    get_runtime_subdir,
+    get_workspace_path,
+)
 from nanobot.config.schema import Config
 
-__all__ = ["Config", "load_config", "get_config_path"]
+__all__ = [
+    "Config",
+    "load_config",
+    "get_config_path",
+    "get_data_dir",
+    "get_runtime_subdir",
+    "get_media_dir",
+    "get_cron_dir",
+    "get_logs_dir",
+    "get_workspace_path",
+    "get_cli_history_path",
+    "get_bridge_install_dir",
+    "get_legacy_sessions_dir",
+]

nanobot/config/loader.py

@@ -6,17 +6,23 @@ from pathlib import Path
 from nanobot.config.schema import Config
 
 
+# Global variable to store current config path (for multi-instance support)
+_current_config_path: Path | None = None
+
+
+def set_config_path(path: Path) -> None:
+    """Set the current config path (used to derive data directory)."""
+    global _current_config_path
+    _current_config_path = path
+
+
 def get_config_path() -> Path:
-    """Get the default configuration file path."""
+    """Get the configuration file path."""
+    if _current_config_path:
+        return _current_config_path
     return Path.home() / ".nanobot" / "config.json"
 
 
-def get_data_dir() -> Path:
-    """Get the nanobot data directory."""
-    from nanobot.utils.helpers import get_data_path
-    return get_data_path()
-
-
 def load_config(config_path: Path | None = None) -> Config:
     """
     Load configuration from file or create default.

nanobot/config/paths.py

@@ -0,0 +1,55 @@
+"""Runtime path helpers derived from the active config context."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from nanobot.config.loader import get_config_path
+from nanobot.utils.helpers import ensure_dir
+
+
+def get_data_dir() -> Path:
+    """Return the instance-level runtime data directory."""
+    return ensure_dir(get_config_path().parent)
+
+
+def get_runtime_subdir(name: str) -> Path:
+    """Return a named runtime subdirectory under the instance data dir."""
+    return ensure_dir(get_data_dir() / name)
+
+
+def get_media_dir(channel: str | None = None) -> Path:
+    """Return the media directory, optionally namespaced per channel."""
+    base = get_runtime_subdir("media")
+    return ensure_dir(base / channel) if channel else base
+
+
+def get_cron_dir() -> Path:
+    """Return the cron storage directory."""
+    return get_runtime_subdir("cron")
+
+
+def get_logs_dir() -> Path:
+    """Return the logs directory."""
+    return get_runtime_subdir("logs")
+
+
+def get_workspace_path(workspace: str | None = None) -> Path:
+    """Resolve and ensure the agent workspace path."""
+    path = Path(workspace).expanduser() if workspace else Path.home() / ".nanobot" / "workspace"
+    return ensure_dir(path)
+
+
+def get_cli_history_path() -> Path:
+    """Return the shared CLI history file path."""
+    return Path.home() / ".nanobot" / "history" / "cli_history"
+
+
+def get_bridge_install_dir() -> Path:
+    """Return the shared WhatsApp bridge installation directory."""
+    return Path.home() / ".nanobot" / "bridge"
+
+
+def get_legacy_sessions_dir() -> Path:
+    """Return the legacy global session directory used for migration fallback."""
+    return Path.home() / ".nanobot" / "sessions"

nanobot/config/schema.py

@@ -29,8 +29,11 @@ class TelegramConfig(Base):
     enabled: bool = False
     token: str = ""  # Bot token from @BotFather
     allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs or usernames
-    proxy: str | None = None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    proxy: str | None = (
+        None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    )
     reply_to_message: bool = False  # If true, bot replies quote the original message
+    group_policy: Literal["open", "mention"] = "mention"  # "mention" responds when @mentioned or replied to, "open" responds to all
 
 
 class FeishuConfig(Base):
@@ -42,7 +45,9 @@ class FeishuConfig(Base):
     encrypt_key: str = ""  # Encrypt Key for event subscription (optional)
     verification_token: str = ""  # Verification Token for event subscription (optional)
     allow_from: list[str] = Field(default_factory=list)  # Allowed user open_ids
-    react_emoji: str = "THUMBSUP"  # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
+    react_emoji: str = (
+        "THUMBSUP"  # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
+    )
 
 
 class DingTalkConfig(Base):
@@ -62,6 +67,7 @@ class DiscordConfig(Base):
     allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs
     gateway_url: str = "wss://gateway.discord.gg/?v=10&encoding=json"
     intents: int = 37377  # GUILDS + GUILD_MESSAGES + DIRECT_MESSAGES + MESSAGE_CONTENT
+    group_policy: Literal["mention", "open"] = "mention"
 
 
 class MatrixConfig(Base):
@@ -72,9 +78,13 @@ class MatrixConfig(Base):
     access_token: str = ""
     user_id: str = ""  # @bot:matrix.org
     device_id: str = ""
-    e2ee_enabled: bool = True # Enable Matrix E2EE support (encryption + encrypted room handling).
+    e2ee_enabled: bool = True  # Enable Matrix E2EE support (encryption + encrypted room handling).
-    sync_stop_grace_seconds: int = 2 # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
+    sync_stop_grace_seconds: int = (
-    max_media_bytes: int = 20 * 1024 * 1024 # Max attachment size accepted for Matrix media handling (inbound + outbound).
+        2  # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
+    )
+    max_media_bytes: int = (
+        20 * 1024 * 1024
+    )  # Max attachment size accepted for Matrix media handling (inbound + outbound).
     allow_from: list[str] = Field(default_factory=list)
     group_policy: Literal["open", "mention", "allowlist"] = "open"
     group_allow_from: list[str] = Field(default_factory=list)
@@ -105,7 +115,9 @@ class EmailConfig(Base):
     from_address: str = ""
 
     # Behavior
-    auto_reply_enabled: bool = True  # If false, inbound email is read but no automatic reply is sent
+    auto_reply_enabled: bool = (
+        True  # If false, inbound email is read but no automatic reply is sent
+    )
     poll_interval_seconds: int = 30
     mark_seen: bool = True
     max_body_chars: int = 12000
@@ -183,27 +195,25 @@ class QQConfig(Base):
     enabled: bool = False
     app_id: str = ""  # 机器人 ID (AppID) from q.qq.com
     secret: str = ""  # 机器人密钥 (AppSecret) from q.qq.com
-    allow_from: list[str] = Field(default_factory=list)  # Allowed user openids (empty = public access)
+    allow_from: list[str] = Field(
+        default_factory=list
+    )  # Allowed user openids (empty = public access)
+
+
+class WecomConfig(Base):
+    """WeCom (Enterprise WeChat) AI Bot channel configuration."""
 
-class MatrixConfig(Base):
-    """Matrix (Element) channel configuration."""
     enabled: bool = False
-    homeserver: str = "https://matrix.org"
+    bot_id: str = ""  # Bot ID from WeCom AI Bot platform
-    access_token: str = ""
+    secret: str = ""  # Bot Secret from WeCom AI Bot platform
-    user_id: str = ""                       # e.g. @bot:matrix.org
+    allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs
-    device_id: str = ""
+    welcome_message: str = ""  # Welcome message for enter_chat event
-    e2ee_enabled: bool = True               # end-to-end encryption support
+
-    sync_stop_grace_seconds: int = 2        # graceful sync_forever shutdown timeout
-    max_media_bytes: int = 20 * 1024 * 1024 # inbound + outbound attachment limit
-    allow_from: list[str] = Field(default_factory=list)
-    group_policy: Literal["open", "mention", "allowlist"] = "open"
-    group_allow_from: list[str] = Field(default_factory=list)
-    allow_room_mentions: bool = False
 
 class ChannelsConfig(Base):
     """Configuration for chat channels."""
 
-    send_progress: bool = True    # stream agent's text progress to the channel
+    send_progress: bool = True  # stream agent's text progress to the channel
     send_tool_hints: bool = False  # stream tool-call hints (e.g. read_file("…"))
     whatsapp: WhatsAppConfig = Field(default_factory=WhatsAppConfig)
     telegram: TelegramConfig = Field(default_factory=TelegramConfig)
@@ -215,6 +225,7 @@ class ChannelsConfig(Base):
     slack: SlackConfig = Field(default_factory=SlackConfig)
     qq: QQConfig = Field(default_factory=QQConfig)
     matrix: MatrixConfig = Field(default_factory=MatrixConfig)
+    wecom: WecomConfig = Field(default_factory=WecomConfig)
 
 
 class AgentDefaults(Base):
@@ -222,13 +233,22 @@ class AgentDefaults(Base):
 
     workspace: str = "~/.nanobot/workspace"
     model: str = "anthropic/claude-opus-4-5"
-    provider: str = "auto"  # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
+    provider: str = (
+        "auto"  # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
+    )
     max_tokens: int = 8192
+    context_window_tokens: int = 65_536
     temperature: float = 0.1
     max_tool_iterations: int = 40
-    memory_window: int = 100
+    # Deprecated compatibility field: accepted from old configs but ignored at runtime.
+    memory_window: int | None = Field(default=None, exclude=True)
     reasoning_effort: str | None = None  # low / medium / high — enables LLM thinking mode
 
+    @property
+    def should_warn_deprecated_memory_window(self) -> bool:
+        """Return True when old memoryWindow is present without contextWindowTokens."""
+        return self.memory_window is not None and "context_window_tokens" not in self.model_fields_set
+
 
 class AgentsConfig(Base):
     """Agent configuration."""
@@ -248,6 +268,7 @@ class ProvidersConfig(Base):
     """Configuration for LLM providers."""
 
     custom: ProviderConfig = Field(default_factory=ProviderConfig)  # Any OpenAI-compatible endpoint
+    azure_openai: ProviderConfig = Field(default_factory=ProviderConfig)  # Azure OpenAI (model = deployment name)
     anthropic: ProviderConfig = Field(default_factory=ProviderConfig)
     openai: ProviderConfig = Field(default_factory=ProviderConfig)
     openrouter: ProviderConfig = Field(default_factory=ProviderConfig)
@@ -260,8 +281,9 @@ class ProvidersConfig(Base):
     moonshot: ProviderConfig = Field(default_factory=ProviderConfig)
     minimax: ProviderConfig = Field(default_factory=ProviderConfig)
     aihubmix: ProviderConfig = Field(default_factory=ProviderConfig)  # AiHubMix API gateway
-    siliconflow: ProviderConfig = Field(default_factory=ProviderConfig)  # SiliconFlow (硅基流动) API gateway
+    ollama: ProviderConfig = Field(default_factory=ProviderConfig)  # Ollama local models
-    volcengine: ProviderConfig = Field(default_factory=ProviderConfig)  # VolcEngine (火山引擎) API gateway
+    siliconflow: ProviderConfig = Field(default_factory=ProviderConfig)  # SiliconFlow (硅基流动)
+    volcengine: ProviderConfig = Field(default_factory=ProviderConfig)  # VolcEngine (火山引擎)
     openai_codex: ProviderConfig = Field(default_factory=ProviderConfig)  # OpenAI Codex (OAuth)
     github_copilot: ProviderConfig = Field(default_factory=ProviderConfig)  # Github Copilot (OAuth)
 
@@ -291,7 +313,9 @@ class WebSearchConfig(Base):
 class WebToolsConfig(Base):
     """Web tools configuration."""
 
-    proxy: str | None = None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    proxy: str | None = (
+        None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    )
     search: WebSearchConfig = Field(default_factory=WebSearchConfig)
 
 
@@ -305,12 +329,13 @@ class ExecToolConfig(Base):
 class MCPServerConfig(Base):
     """MCP server connection configuration (stdio or HTTP)."""
 
+    type: Literal["stdio", "sse", "streamableHttp"] | None = None  # auto-detected if omitted
     command: str = ""  # Stdio: command to run (e.g. "npx")
     args: list[str] = Field(default_factory=list)  # Stdio: command arguments
     env: dict[str, str] = Field(default_factory=dict)  # Stdio: extra env vars
-    url: str = ""  # HTTP: streamable HTTP endpoint URL
+    url: str = ""  # HTTP/SSE: endpoint URL
-    headers: dict[str, str] = Field(default_factory=dict)  # HTTP: Custom HTTP Headers
+    headers: dict[str, str] = Field(default_factory=dict)  # HTTP/SSE: custom headers
-    tool_timeout: int = 30  # Seconds before a tool call is cancelled
+    tool_timeout: int = 30  # seconds before a tool call is cancelled
 
 
 class ToolsConfig(Base):
@@ -336,7 +361,9 @@ class Config(BaseSettings):
         """Get expanded workspace path."""
         return Path(self.agents.defaults.workspace).expanduser()
 
-    def _match_provider(self, model: str | None = None) -> tuple["ProviderConfig | None", str | None]:
+    def _match_provider(
+        self, model: str | None = None
+    ) -> tuple["ProviderConfig | None", str | None]:
         """Match provider config and its registry name. Returns (config, spec_name)."""
         from nanobot.providers.registry import PROVIDERS
 
@@ -358,16 +385,25 @@ class Config(BaseSettings):
         for spec in PROVIDERS:
             p = getattr(self.providers, spec.name, None)
             if p and model_prefix and normalized_prefix == spec.name:
-                if spec.is_oauth or p.api_key:
+                if spec.is_oauth or spec.is_local or p.api_key:
                     return p, spec.name
 
         # Match by keyword (order follows PROVIDERS registry)
         for spec in PROVIDERS:
             p = getattr(self.providers, spec.name, None)
             if p and any(_kw_matches(kw) for kw in spec.keywords):
-                if spec.is_oauth or p.api_key:
+                if spec.is_oauth or spec.is_local or p.api_key:
                     return p, spec.name
 
+        # Fallback: configured local providers can route models without
+        # provider-specific keywords (for example plain "llama3.2" on Ollama).
+        for spec in PROVIDERS:
+            if not spec.is_local:
+                continue
+            p = getattr(self.providers, spec.name, None)
+            if p and p.api_base:
+                return p, spec.name
+
         # Fallback: gateways first, then others (follows registry order)
         # OAuth providers are NOT valid fallbacks — they require explicit model selection
         for spec in PROVIDERS:
@@ -394,7 +430,7 @@ class Config(BaseSettings):
         return p.api_key if p else None
 
     def get_api_base(self, model: str | None = None) -> str | None:
-        """Get API base URL for the given model. Applies default URLs for known gateways."""
+        """Get API base URL for the given model. Applies default URLs for gateway/local providers."""
         from nanobot.providers.registry import find_by_name
 
         p, name = self._match_provider(model)
@@ -405,7 +441,7 @@ class Config(BaseSettings):
         # to avoid polluting the global litellm.api_base.
         if name:
             spec = find_by_name(name)
-            if spec and spec.is_gateway and spec.default_api_base:
+            if spec and (spec.is_gateway or spec.is_local) and spec.default_api_base:
                 return spec.default_api_base
         return None
 

nanobot/heartbeat/service.py

@@ -87,7 +87,7 @@ class HeartbeatService:
 
         Returns (action, tasks) where action is 'skip' or 'run'.
         """
-        response = await self.provider.chat(
+        response = await self.provider.chat_with_retry(
             messages=[
                 {"role": "system", "content": "You are a heartbeat agent. Call the heartbeat tool to report your decision."},
                 {"role": "user", "content": (

nanobot/providers/__init__.py

@@ -3,5 +3,6 @@
 from nanobot.providers.base import LLMProvider, LLMResponse
 from nanobot.providers.litellm_provider import LiteLLMProvider
 from nanobot.providers.openai_codex_provider import OpenAICodexProvider
+from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
 
-__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider"]
+__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider", "AzureOpenAIProvider"]

nanobot/providers/azure_openai_provider.py

@@ -0,0 +1,210 @@
+"""Azure OpenAI provider implementation with API version 2024-10-21."""
+
+from __future__ import annotations
+
+import uuid
+from typing import Any
+from urllib.parse import urljoin
+
+import httpx
+import json_repair
+
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+
+_AZURE_MSG_KEYS = frozenset({"role", "content", "tool_calls", "tool_call_id", "name"})
+
+
+class AzureOpenAIProvider(LLMProvider):
+    """
+    Azure OpenAI provider with API version 2024-10-21 compliance.
+    
+    Features:
+    - Hardcoded API version 2024-10-21
+    - Uses model field as Azure deployment name in URL path
+    - Uses api-key header instead of Authorization Bearer
+    - Uses max_completion_tokens instead of max_tokens
+    - Direct HTTP calls, bypasses LiteLLM
+    """
+
+    def __init__(
+        self,
+        api_key: str = "",
+        api_base: str = "",
+        default_model: str = "gpt-5.2-chat",
+    ):
+        super().__init__(api_key, api_base)
+        self.default_model = default_model
+        self.api_version = "2024-10-21"
+        
+        # Validate required parameters
+        if not api_key:
+            raise ValueError("Azure OpenAI api_key is required")
+        if not api_base:
+            raise ValueError("Azure OpenAI api_base is required")
+        
+        # Ensure api_base ends with /
+        if not api_base.endswith('/'):
+            api_base += '/'
+        self.api_base = api_base
+
+    def _build_chat_url(self, deployment_name: str) -> str:
+        """Build the Azure OpenAI chat completions URL."""
+        # Azure OpenAI URL format:
+        # https://{resource}.openai.azure.com/openai/deployments/{deployment}/chat/completions?api-version={version}
+        base_url = self.api_base
+        if not base_url.endswith('/'):
+            base_url += '/'
+        
+        url = urljoin(
+            base_url, 
+            f"openai/deployments/{deployment_name}/chat/completions"
+        )
+        return f"{url}?api-version={self.api_version}"
+
+    def _build_headers(self) -> dict[str, str]:
+        """Build headers for Azure OpenAI API with api-key header."""
+        return {
+            "Content-Type": "application/json",
+            "api-key": self.api_key,  # Azure OpenAI uses api-key header, not Authorization
+            "x-session-affinity": uuid.uuid4().hex,  # For cache locality
+        }
+
+    @staticmethod
+    def _supports_temperature(
+        deployment_name: str,
+        reasoning_effort: str | None = None,
+    ) -> bool:
+        """Return True when temperature is likely supported for this deployment."""
+        if reasoning_effort:
+            return False
+        name = deployment_name.lower()
+        return not any(token in name for token in ("gpt-5", "o1", "o3", "o4"))
+
+    def _prepare_request_payload(
+        self,
+        deployment_name: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.7,
+        reasoning_effort: str | None = None,
+    ) -> dict[str, Any]:
+        """Prepare the request payload with Azure OpenAI 2024-10-21 compliance."""
+        payload: dict[str, Any] = {
+            "messages": self._sanitize_request_messages(
+                self._sanitize_empty_content(messages),
+                _AZURE_MSG_KEYS,
+            ),
+            "max_completion_tokens": max(1, max_tokens),  # Azure API 2024-10-21 uses max_completion_tokens
+        }
+
+        if self._supports_temperature(deployment_name, reasoning_effort):
+            payload["temperature"] = temperature
+
+        if reasoning_effort:
+            payload["reasoning_effort"] = reasoning_effort
+
+        if tools:
+            payload["tools"] = tools
+            payload["tool_choice"] = "auto"
+
+        return payload
+
+    async def chat(
+        self,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        model: str | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.7,
+        reasoning_effort: str | None = None,
+    ) -> LLMResponse:
+        """
+        Send a chat completion request to Azure OpenAI.
+
+        Args:
+            messages: List of message dicts with 'role' and 'content'.
+            tools: Optional list of tool definitions in OpenAI format.
+            model: Model identifier (used as deployment name).
+            max_tokens: Maximum tokens in response (mapped to max_completion_tokens).
+            temperature: Sampling temperature.
+            reasoning_effort: Optional reasoning effort parameter.
+
+        Returns:
+            LLMResponse with content and/or tool calls.
+        """
+        deployment_name = model or self.default_model
+        url = self._build_chat_url(deployment_name)
+        headers = self._build_headers()
+        payload = self._prepare_request_payload(
+            deployment_name, messages, tools, max_tokens, temperature, reasoning_effort
+        )
+
+        try:
+            async with httpx.AsyncClient(timeout=60.0, verify=True) as client:
+                response = await client.post(url, headers=headers, json=payload)
+                if response.status_code != 200:
+                    return LLMResponse(
+                        content=f"Azure OpenAI API Error {response.status_code}: {response.text}",
+                        finish_reason="error",
+                    )
+                
+                response_data = response.json()
+                return self._parse_response(response_data)
+
+        except Exception as e:
+            return LLMResponse(
+                content=f"Error calling Azure OpenAI: {repr(e)}",
+                finish_reason="error",
+            )
+
+    def _parse_response(self, response: dict[str, Any]) -> LLMResponse:
+        """Parse Azure OpenAI response into our standard format."""
+        try:
+            choice = response["choices"][0]
+            message = choice["message"]
+
+            tool_calls = []
+            if message.get("tool_calls"):
+                for tc in message["tool_calls"]:
+                    # Parse arguments from JSON string if needed
+                    args = tc["function"]["arguments"]
+                    if isinstance(args, str):
+                        args = json_repair.loads(args)
+
+                    tool_calls.append(
+                        ToolCallRequest(
+                            id=tc["id"],
+                            name=tc["function"]["name"],
+                            arguments=args,
+                        )
+                    )
+
+            usage = {}
+            if response.get("usage"):
+                usage_data = response["usage"]
+                usage = {
+                    "prompt_tokens": usage_data.get("prompt_tokens", 0),
+                    "completion_tokens": usage_data.get("completion_tokens", 0),
+                    "total_tokens": usage_data.get("total_tokens", 0),
+                }
+
+            reasoning_content = message.get("reasoning_content") or None
+
+            return LLMResponse(
+                content=message.get("content"),
+                tool_calls=tool_calls,
+                finish_reason=choice.get("finish_reason", "stop"),
+                usage=usage,
+                reasoning_content=reasoning_content,
+            )
+
+        except (KeyError, IndexError) as e:
+            return LLMResponse(
+                content=f"Error parsing Azure OpenAI response: {str(e)}",
+                finish_reason="error",
+            )
+
+    def get_default_model(self) -> str:
+        """Get the default model (also used as default deployment name)."""
+        return self.default_model

nanobot/providers/base.py

@@ -1,9 +1,13 @@
 """Base LLM provider interface."""
 
+import asyncio
+import json
 from abc import ABC, abstractmethod
 from dataclasses import dataclass, field
 from typing import Any
 
+from loguru import logger
+
 
 @dataclass
 class ToolCallRequest:
@@ -11,6 +15,24 @@ class ToolCallRequest:
     id: str
     name: str
     arguments: dict[str, Any]
+    provider_specific_fields: dict[str, Any] | None = None
+    function_provider_specific_fields: dict[str, Any] | None = None
+
+    def to_openai_tool_call(self) -> dict[str, Any]:
+        """Serialize to an OpenAI-style tool_call payload."""
+        tool_call = {
+            "id": self.id,
+            "type": "function",
+            "function": {
+                "name": self.name,
+                "arguments": json.dumps(self.arguments, ensure_ascii=False),
+            },
+        }
+        if self.provider_specific_fields:
+            tool_call["provider_specific_fields"] = self.provider_specific_fields
+        if self.function_provider_specific_fields:
+            tool_call["function"]["provider_specific_fields"] = self.function_provider_specific_fields
+        return tool_call
 
 
 @dataclass
@@ -29,6 +51,21 @@ class LLMResponse:
         return len(self.tool_calls) > 0
 
 
+@dataclass(frozen=True)
+class GenerationSettings:
+    """Default generation parameters for LLM calls.
+
+    Stored on the provider so every call site inherits the same defaults
+    without having to pass temperature / max_tokens / reasoning_effort
+    through every layer.  Individual call sites can still override by
+    passing explicit keyword arguments to chat() / chat_with_retry().
+    """
+
+    temperature: float = 0.7
+    max_tokens: int = 4096
+    reasoning_effort: str | None = None
+
+
 class LLMProvider(ABC):
     """
     Abstract base class for LLM providers.
@@ -37,9 +74,28 @@ class LLMProvider(ABC):
     while maintaining a consistent interface.
     """
 
+    _CHAT_RETRY_DELAYS = (1, 2, 4)
+    _TRANSIENT_ERROR_MARKERS = (
+        "429",
+        "rate limit",
+        "500",
+        "502",
+        "503",
+        "504",
+        "overloaded",
+        "timeout",
+        "timed out",
+        "connection",
+        "server error",
+        "temporarily unavailable",
+    )
+
+    _SENTINEL = object()
+
     def __init__(self, api_key: str | None = None, api_base: str | None = None):
         self.api_key = api_key
         self.api_base = api_base
+        self.generation: GenerationSettings = GenerationSettings()
 
     @staticmethod
     def _sanitize_empty_content(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
@@ -87,6 +143,20 @@ class LLMProvider(ABC):
             result.append(msg)
         return result
 
+    @staticmethod
+    def _sanitize_request_messages(
+        messages: list[dict[str, Any]],
+        allowed_keys: frozenset[str],
+    ) -> list[dict[str, Any]]:
+        """Keep only provider-safe message keys and normalize assistant content."""
+        sanitized = []
+        for msg in messages:
+            clean = {k: v for k, v in msg.items() if k in allowed_keys}
+            if clean.get("role") == "assistant" and "content" not in clean:
+                clean["content"] = None
+            sanitized.append(clean)
+        return sanitized
+
     @abstractmethod
     async def chat(
         self,
@@ -112,6 +182,83 @@ class LLMProvider(ABC):
         """
         pass
 
+    @classmethod
+    def _is_transient_error(cls, content: str | None) -> bool:
+        err = (content or "").lower()
+        return any(marker in err for marker in cls._TRANSIENT_ERROR_MARKERS)
+
+    async def chat_with_retry(
+        self,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        model: str | None = None,
+        max_tokens: object = _SENTINEL,
+        temperature: object = _SENTINEL,
+        reasoning_effort: object = _SENTINEL,
+    ) -> LLMResponse:
+        """Call chat() with retry on transient provider failures.
+
+        Parameters default to ``self.generation`` when not explicitly passed,
+        so callers no longer need to thread temperature / max_tokens /
+        reasoning_effort through every layer.
+        """
+        if max_tokens is self._SENTINEL:
+            max_tokens = self.generation.max_tokens
+        if temperature is self._SENTINEL:
+            temperature = self.generation.temperature
+        if reasoning_effort is self._SENTINEL:
+            reasoning_effort = self.generation.reasoning_effort
+
+        for attempt, delay in enumerate(self._CHAT_RETRY_DELAYS, start=1):
+            try:
+                response = await self.chat(
+                    messages=messages,
+                    tools=tools,
+                    model=model,
+                    max_tokens=max_tokens,
+                    temperature=temperature,
+                    reasoning_effort=reasoning_effort,
+                )
+            except asyncio.CancelledError:
+                raise
+            except Exception as exc:
+                response = LLMResponse(
+                    content=f"Error calling LLM: {exc}",
+                    finish_reason="error",
+                )
+
+            if response.finish_reason != "error":
+                return response
+            if not self._is_transient_error(response.content):
+                return response
+
+            err = (response.content or "").lower()
+            logger.warning(
+                "LLM transient error (attempt {}/{}), retrying in {}s: {}",
+                attempt,
+                len(self._CHAT_RETRY_DELAYS),
+                delay,
+                err[:120],
+            )
+            await asyncio.sleep(delay)
+
+        try:
+            return await self.chat(
+                messages=messages,
+                tools=tools,
+                model=model,
+                max_tokens=max_tokens,
+                temperature=temperature,
+                reasoning_effort=reasoning_effort,
+            )
+        except asyncio.CancelledError:
+            raise
+        except Exception as exc:
+            return LLMResponse(
+                content=f"Error calling LLM: {exc}",
+                finish_reason="error",
+            )
+
     @abstractmethod
     def get_default_model(self) -> str:
         """Get the default model for this provider."""

nanobot/providers/custom_provider.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import uuid
 from typing import Any
 
 import json_repair
@@ -15,7 +16,12 @@ class CustomProvider(LLMProvider):
     def __init__(self, api_key: str = "no-key", api_base: str = "http://localhost:8000/v1", default_model: str = "default"):
         super().__init__(api_key, api_base)
         self.default_model = default_model
-        self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
+        # Keep affinity stable for this provider instance to improve backend cache locality.
+        self._client = AsyncOpenAI(
+            api_key=api_key,
+            base_url=api_base,
+            default_headers={"x-session-affinity": uuid.uuid4().hex},
+        )
 
     async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
                    model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7,

nanobot/providers/litellm_provider.py

@@ -1,5 +1,6 @@
 """LiteLLM provider implementation for multi-provider support."""
 
+import hashlib
 import os
 import secrets
 import string
@@ -8,6 +9,7 @@ from typing import Any
 import json_repair
 import litellm
 from litellm import acompletion
+from loguru import logger
 
 from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
 from nanobot.providers.registry import find_by_model, find_gateway
@@ -165,17 +167,43 @@ class LiteLLMProvider(LLMProvider):
             return _ANTHROPIC_EXTRA_KEYS
         return frozenset()
 
+    @staticmethod
+    def _normalize_tool_call_id(tool_call_id: Any) -> Any:
+        """Normalize tool_call_id to a provider-safe 9-char alphanumeric form."""
+        if not isinstance(tool_call_id, str):
+            return tool_call_id
+        if len(tool_call_id) == 9 and tool_call_id.isalnum():
+            return tool_call_id
+        return hashlib.sha1(tool_call_id.encode()).hexdigest()[:9]
+
     @staticmethod
     def _sanitize_messages(messages: list[dict[str, Any]], extra_keys: frozenset[str] = frozenset()) -> list[dict[str, Any]]:
         """Strip non-standard keys and ensure assistant messages have a content key."""
         allowed = _ALLOWED_MSG_KEYS | extra_keys
-        sanitized = []
+        sanitized = LLMProvider._sanitize_request_messages(messages, allowed)
-        for msg in messages:
+        id_map: dict[str, str] = {}
-            clean = {k: v for k, v in msg.items() if k in allowed}
+
-            # Strict providers require "content" even when assistant only has tool_calls
+        def map_id(value: Any) -> Any:
-            if clean.get("role") == "assistant" and "content" not in clean:
+            if not isinstance(value, str):
-                clean["content"] = None
+                return value
-            sanitized.append(clean)
+            return id_map.setdefault(value, LiteLLMProvider._normalize_tool_call_id(value))
+
+        for clean in sanitized:
+            # Keep assistant tool_calls[].id and tool tool_call_id in sync after
+            # shortening, otherwise strict providers reject the broken linkage.
+            if isinstance(clean.get("tool_calls"), list):
+                normalized_tool_calls = []
+                for tc in clean["tool_calls"]:
+                    if not isinstance(tc, dict):
+                        normalized_tool_calls.append(tc)
+                        continue
+                    tc_clean = dict(tc)
+                    tc_clean["id"] = map_id(tc_clean.get("id"))
+                    normalized_tool_calls.append(tc_clean)
+                clean["tool_calls"] = normalized_tool_calls
+
+            if "tool_call_id" in clean and clean["tool_call_id"]:
+                clean["tool_call_id"] = map_id(clean["tool_call_id"])
         return sanitized
 
     async def chat(
@@ -255,20 +283,44 @@ class LiteLLMProvider(LLMProvider):
         """Parse LiteLLM response into our standard format."""
         choice = response.choices[0]
         message = choice.message
+        content = message.content
+        finish_reason = choice.finish_reason
+
+        # Some providers (e.g. GitHub Copilot) split content and tool_calls
+        # across multiple choices. Merge them so tool_calls are not lost.
+        raw_tool_calls = []
+        for ch in response.choices:
+            msg = ch.message
+            if hasattr(msg, "tool_calls") and msg.tool_calls:
+                raw_tool_calls.extend(msg.tool_calls)
+                if ch.finish_reason in ("tool_calls", "stop"):
+                    finish_reason = ch.finish_reason
+            if not content and msg.content:
+                content = msg.content
+
+        if len(response.choices) > 1:
+            logger.debug("LiteLLM response has {} choices, merged {} tool_calls",
+                         len(response.choices), len(raw_tool_calls))
 
         tool_calls = []
-        if hasattr(message, "tool_calls") and message.tool_calls:
+        for tc in raw_tool_calls:
-            for tc in message.tool_calls:
+            # Parse arguments from JSON string if needed
-                # Parse arguments from JSON string if needed
+            args = tc.function.arguments
-                args = tc.function.arguments
+            if isinstance(args, str):
-                if isinstance(args, str):
+                args = json_repair.loads(args)
-                    args = json_repair.loads(args)
 
-                tool_calls.append(ToolCallRequest(
+            provider_specific_fields = getattr(tc, "provider_specific_fields", None) or None
-                    id=_short_tool_id(),
+            function_provider_specific_fields = (
-                    name=tc.function.name,
+                getattr(tc.function, "provider_specific_fields", None) or None
-                    arguments=args,
+            )
-                ))
+
+            tool_calls.append(ToolCallRequest(
+                id=_short_tool_id(),
+                name=tc.function.name,
+                arguments=args,
+                provider_specific_fields=provider_specific_fields,
+                function_provider_specific_fields=function_provider_specific_fields,
+            ))
 
         usage = {}
         if hasattr(response, "usage") and response.usage:
@@ -280,11 +332,11 @@ class LiteLLMProvider(LLMProvider):
 
         reasoning_content = getattr(message, "reasoning_content", None) or None
         thinking_blocks = getattr(message, "thinking_blocks", None) or None
-        
+
         return LLMResponse(
-            content=message.content,
+            content=content,
             tool_calls=tool_calls,
-            finish_reason=choice.finish_reason or "stop",
+            finish_reason=finish_reason or "stop",
             usage=usage,
             reasoning_content=reasoning_content,
             thinking_blocks=thinking_blocks,

nanobot/providers/openai_codex_provider.py

@@ -52,6 +52,9 @@ class OpenAICodexProvider(LLMProvider):
             "parallel_tool_calls": True,
         }
 
+        if reasoning_effort:
+            body["reasoning"] = {"effort": reasoning_effort}
+
         if tools:
             body["tools"] = _convert_tools(tools)
 

nanobot/providers/registry.py

@@ -26,33 +26,33 @@ class ProviderSpec:
     """
 
     # identity
-    name: str                       # config field name, e.g. "dashscope"
+    name: str  # config field name, e.g. "dashscope"
-    keywords: tuple[str, ...]       # model-name keywords for matching (lowercase)
+    keywords: tuple[str, ...]  # model-name keywords for matching (lowercase)
-    env_key: str                    # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
+    env_key: str  # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
-    display_name: str = ""          # shown in `nanobot status`
+    display_name: str = ""  # shown in `nanobot status`
 
     # model prefixing
-    litellm_prefix: str = ""                 # "dashscope" → model becomes "dashscope/{model}"
+    litellm_prefix: str = ""  # "dashscope" → model becomes "dashscope/{model}"
-    skip_prefixes: tuple[str, ...] = ()      # don't prefix if model already starts with these
+    skip_prefixes: tuple[str, ...] = ()  # don't prefix if model already starts with these
 
     # extra env vars, e.g. (("ZHIPUAI_API_KEY", "{api_key}"),)
     env_extras: tuple[tuple[str, str], ...] = ()
 
     # gateway / local detection
-    is_gateway: bool = False                 # routes any model (OpenRouter, AiHubMix)
+    is_gateway: bool = False  # routes any model (OpenRouter, AiHubMix)
-    is_local: bool = False                   # local deployment (vLLM, Ollama)
+    is_local: bool = False  # local deployment (vLLM, Ollama)
-    detect_by_key_prefix: str = ""           # match api_key prefix, e.g. "sk-or-"
+    detect_by_key_prefix: str = ""  # match api_key prefix, e.g. "sk-or-"
-    detect_by_base_keyword: str = ""         # match substring in api_base URL
+    detect_by_base_keyword: str = ""  # match substring in api_base URL
-    default_api_base: str = ""               # fallback base URL
+    default_api_base: str = ""  # fallback base URL
 
     # gateway behavior
-    strip_model_prefix: bool = False         # strip "provider/" before re-prefixing
+    strip_model_prefix: bool = False  # strip "provider/" before re-prefixing
 
     # per-model param overrides, e.g. (("kimi-k2.5", {"temperature": 1.0}),)
     model_overrides: tuple[tuple[str, dict[str, Any]], ...] = ()
 
     # OAuth-based providers (e.g., OpenAI Codex) don't use API keys
-    is_oauth: bool = False                   # if True, uses OAuth flow instead of API key
+    is_oauth: bool = False  # if True, uses OAuth flow instead of API key
 
     # Direct providers bypass LiteLLM entirely (e.g., CustomProvider)
     is_direct: bool = False
@@ -70,7 +70,6 @@ class ProviderSpec:
 # ---------------------------------------------------------------------------
 
 PROVIDERS: tuple[ProviderSpec, ...] = (
-
     # === Custom (direct OpenAI-compatible endpoint, bypasses LiteLLM) ======
     ProviderSpec(
         name="custom",
@@ -81,16 +80,24 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         is_direct=True,
     ),
 
+    # === Azure OpenAI (direct API calls with API version 2024-10-21) =====
+    ProviderSpec(
+        name="azure_openai",
+        keywords=("azure", "azure-openai"),
+        env_key="",
+        display_name="Azure OpenAI",
+        litellm_prefix="",
+        is_direct=True,
+    ),
     # === Gateways (detected by api_key / api_base, not model name) =========
     # Gateways can route any model, so they win in fallback.
-
     # OpenRouter: global gateway, keys start with "sk-or-"
     ProviderSpec(
         name="openrouter",
         keywords=("openrouter",),
         env_key="OPENROUTER_API_KEY",
         display_name="OpenRouter",
-        litellm_prefix="openrouter",        # claude-3 → openrouter/claude-3
+        litellm_prefix="openrouter",  # claude-3 → openrouter/claude-3
         skip_prefixes=(),
         env_extras=(),
         is_gateway=True,
@@ -102,16 +109,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         model_overrides=(),
         supports_prompt_caching=True,
     ),
-
     # AiHubMix: global gateway, OpenAI-compatible interface.
     # strip_model_prefix=True: it doesn't understand "anthropic/claude-3",
     # so we strip to bare "claude-3" then re-prefix as "openai/claude-3".
     ProviderSpec(
         name="aihubmix",
         keywords=("aihubmix",),
-        env_key="OPENAI_API_KEY",           # OpenAI-compatible
+        env_key="OPENAI_API_KEY",  # OpenAI-compatible
         display_name="AiHubMix",
-        litellm_prefix="openai",            # → openai/{model}
+        litellm_prefix="openai",  # → openai/{model}
         skip_prefixes=(),
         env_extras=(),
         is_gateway=True,
@@ -119,10 +125,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         detect_by_key_prefix="",
         detect_by_base_keyword="aihubmix",
         default_api_base="https://aihubmix.com/v1",
-        strip_model_prefix=True,            # anthropic/claude-3 → claude-3 → openai/claude-3
+        strip_model_prefix=True,  # anthropic/claude-3 → claude-3 → openai/claude-3
         model_overrides=(),
     ),
-
     # SiliconFlow (硅基流动): OpenAI-compatible gateway, model names keep org prefix
     ProviderSpec(
         name="siliconflow",
@@ -140,7 +145,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # VolcEngine (火山引擎): OpenAI-compatible gateway
     ProviderSpec(
         name="volcengine",
@@ -158,9 +162,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # === Standard providers (matched by model-name keywords) ===============
-
     # Anthropic: LiteLLM recognizes "claude-*" natively, no prefix needed.
     ProviderSpec(
         name="anthropic",
@@ -179,7 +181,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         model_overrides=(),
         supports_prompt_caching=True,
     ),
-
     # OpenAI: LiteLLM recognizes "gpt-*" natively, no prefix needed.
     ProviderSpec(
         name="openai",
@@ -197,14 +198,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # OpenAI Codex: uses OAuth, not API key.
     ProviderSpec(
         name="openai_codex",
         keywords=("openai-codex",),
-        env_key="",                         # OAuth-based, no API key
+        env_key="",  # OAuth-based, no API key
         display_name="OpenAI Codex",
-        litellm_prefix="",                  # Not routed through LiteLLM
+        litellm_prefix="",  # Not routed through LiteLLM
         skip_prefixes=(),
         env_extras=(),
         is_gateway=False,
@@ -214,16 +214,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         default_api_base="https://chatgpt.com/backend-api",
         strip_model_prefix=False,
         model_overrides=(),
-        is_oauth=True,                      # OAuth-based authentication
+        is_oauth=True,  # OAuth-based authentication
     ),
-
     # Github Copilot: uses OAuth, not API key.
     ProviderSpec(
         name="github_copilot",
         keywords=("github_copilot", "copilot"),
-        env_key="",                         # OAuth-based, no API key
+        env_key="",  # OAuth-based, no API key
         display_name="Github Copilot",
-        litellm_prefix="github_copilot",   # github_copilot/model → github_copilot/model
+        litellm_prefix="github_copilot",  # github_copilot/model → github_copilot/model
         skip_prefixes=("github_copilot/",),
         env_extras=(),
         is_gateway=False,
@@ -233,17 +232,16 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         default_api_base="",
         strip_model_prefix=False,
         model_overrides=(),
-        is_oauth=True,                      # OAuth-based authentication
+        is_oauth=True,  # OAuth-based authentication
     ),
-
     # DeepSeek: needs "deepseek/" prefix for LiteLLM routing.
     ProviderSpec(
         name="deepseek",
         keywords=("deepseek",),
         env_key="DEEPSEEK_API_KEY",
         display_name="DeepSeek",
-        litellm_prefix="deepseek",          # deepseek-chat → deepseek/deepseek-chat
+        litellm_prefix="deepseek",  # deepseek-chat → deepseek/deepseek-chat
-        skip_prefixes=("deepseek/",),       # avoid double-prefix
+        skip_prefixes=("deepseek/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -253,15 +251,14 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # Gemini: needs "gemini/" prefix for LiteLLM.
     ProviderSpec(
         name="gemini",
         keywords=("gemini",),
         env_key="GEMINI_API_KEY",
         display_name="Gemini",
-        litellm_prefix="gemini",            # gemini-pro → gemini/gemini-pro
+        litellm_prefix="gemini",  # gemini-pro → gemini/gemini-pro
-        skip_prefixes=("gemini/",),         # avoid double-prefix
+        skip_prefixes=("gemini/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -271,7 +268,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # Zhipu: LiteLLM uses "zai/" prefix.
     # Also mirrors key to ZHIPUAI_API_KEY (some LiteLLM paths check that).
     # skip_prefixes: don't add "zai/" when already routed via gateway.
@@ -280,11 +276,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("zhipu", "glm", "zai"),
         env_key="ZAI_API_KEY",
         display_name="Zhipu AI",
-        litellm_prefix="zai",              # glm-4 → zai/glm-4
+        litellm_prefix="zai",  # glm-4 → zai/glm-4
         skip_prefixes=("zhipu/", "zai/", "openrouter/", "hosted_vllm/"),
-        env_extras=(
+        env_extras=(("ZHIPUAI_API_KEY", "{api_key}"),),
-            ("ZHIPUAI_API_KEY", "{api_key}"),
-        ),
         is_gateway=False,
         is_local=False,
         detect_by_key_prefix="",
@@ -293,14 +287,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # DashScope: Qwen models, needs "dashscope/" prefix.
     ProviderSpec(
         name="dashscope",
         keywords=("qwen", "dashscope"),
         env_key="DASHSCOPE_API_KEY",
         display_name="DashScope",
-        litellm_prefix="dashscope",         # qwen-max → dashscope/qwen-max
+        litellm_prefix="dashscope",  # qwen-max → dashscope/qwen-max
         skip_prefixes=("dashscope/", "openrouter/"),
         env_extras=(),
         is_gateway=False,
@@ -311,7 +304,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # Moonshot: Kimi models, needs "moonshot/" prefix.
     # LiteLLM requires MOONSHOT_API_BASE env var to find the endpoint.
     # Kimi K2.5 API enforces temperature >= 1.0.
@@ -320,22 +312,17 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("moonshot", "kimi"),
         env_key="MOONSHOT_API_KEY",
         display_name="Moonshot",
-        litellm_prefix="moonshot",          # kimi-k2.5 → moonshot/kimi-k2.5
+        litellm_prefix="moonshot",  # kimi-k2.5 → moonshot/kimi-k2.5
         skip_prefixes=("moonshot/", "openrouter/"),
-        env_extras=(
+        env_extras=(("MOONSHOT_API_BASE", "{api_base}"),),
-            ("MOONSHOT_API_BASE", "{api_base}"),
-        ),
         is_gateway=False,
         is_local=False,
         detect_by_key_prefix="",
         detect_by_base_keyword="",
-        default_api_base="https://api.moonshot.ai/v1",   # intl; use api.moonshot.cn for China
+        default_api_base="https://api.moonshot.ai/v1",  # intl; use api.moonshot.cn for China
         strip_model_prefix=False,
-        model_overrides=(
+        model_overrides=(("kimi-k2.5", {"temperature": 1.0}),),
-            ("kimi-k2.5", {"temperature": 1.0}),
-        ),
     ),
-
     # MiniMax: needs "minimax/" prefix for LiteLLM routing.
     # Uses OpenAI-compatible API at api.minimax.io/v1.
     ProviderSpec(
@@ -343,7 +330,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("minimax",),
         env_key="MINIMAX_API_KEY",
         display_name="MiniMax",
-        litellm_prefix="minimax",            # MiniMax-M2.1 → minimax/MiniMax-M2.1
+        litellm_prefix="minimax",  # MiniMax-M2.1 → minimax/MiniMax-M2.1
         skip_prefixes=("minimax/", "openrouter/"),
         env_extras=(),
         is_gateway=False,
@@ -354,9 +341,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # === Local deployment (matched by config key, NOT by api_base) =========
-
     # vLLM / any OpenAI-compatible local server.
     # Detected when config key is "vllm" (provider_name="vllm").
     ProviderSpec(
@@ -364,20 +349,35 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("vllm",),
         env_key="HOSTED_VLLM_API_KEY",
         display_name="vLLM/Local",
-        litellm_prefix="hosted_vllm",      # Llama-3-8B → hosted_vllm/Llama-3-8B
+        litellm_prefix="hosted_vllm",  # Llama-3-8B → hosted_vllm/Llama-3-8B
         skip_prefixes=(),
         env_extras=(),
         is_gateway=False,
         is_local=True,
         detect_by_key_prefix="",
         detect_by_base_keyword="",
-        default_api_base="",                # user must provide in config
+        default_api_base="",  # user must provide in config
+        strip_model_prefix=False,
+        model_overrides=(),
+    ),
+    # === Ollama (local, OpenAI-compatible) ===================================
+    ProviderSpec(
+        name="ollama",
+        keywords=("ollama", "nemotron"),
+        env_key="OLLAMA_API_KEY",
+        display_name="Ollama",
+        litellm_prefix="ollama_chat",  # model → ollama_chat/model
+        skip_prefixes=("ollama/", "ollama_chat/"),
+        env_extras=(),
+        is_gateway=False,
+        is_local=True,
+        detect_by_key_prefix="",
+        detect_by_base_keyword="11434",
+        default_api_base="http://localhost:11434",
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # === Auxiliary (not a primary LLM provider) ============================
-
     # Groq: mainly used for Whisper voice transcription, also usable for LLM.
     # Needs "groq/" prefix for LiteLLM routing. Placed last — it rarely wins fallback.
     ProviderSpec(
@@ -385,8 +385,8 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("groq",),
         env_key="GROQ_API_KEY",
         display_name="Groq",
-        litellm_prefix="groq",              # llama3-8b-8192 → groq/llama3-8b-8192
+        litellm_prefix="groq",  # llama3-8b-8192 → groq/llama3-8b-8192
-        skip_prefixes=("groq/",),           # avoid double-prefix
+        skip_prefixes=("groq/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -403,6 +403,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
 # Lookup helpers
 # ---------------------------------------------------------------------------
 
+
 def find_by_model(model: str) -> ProviderSpec | None:
     """Match a standard provider by model-name keyword (case-insensitive).
     Skips gateways/local — those are matched by api_key/api_base instead."""
@@ -418,7 +419,9 @@ def find_by_model(model: str) -> ProviderSpec | None:
             return spec
 
     for spec in std_specs:
-        if any(kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords):
+        if any(
+            kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords
+        ):
             return spec
     return None
 

nanobot/session/manager.py

@@ -9,6 +9,7 @@ from typing import Any
 
 from loguru import logger
 
+from nanobot.config.paths import get_legacy_sessions_dir
 from nanobot.utils.helpers import ensure_dir, safe_filename
 
 
@@ -79,7 +80,7 @@ class SessionManager:
     def __init__(self, workspace: Path):
         self.workspace = workspace
         self.sessions_dir = ensure_dir(self.workspace / "sessions")
-        self.legacy_sessions_dir = Path.home() / ".nanobot" / "sessions"
+        self.legacy_sessions_dir = get_legacy_sessions_dir()
         self._cache: dict[str, Session] = {}
 
     def _get_session_path(self, key: str) -> Path:

nanobot/skills/memory/SKILL.md

@@ -9,15 +9,21 @@ always: true
 ## Structure
 
 - `memory/MEMORY.md` — Long-term facts (preferences, project context, relationships). Always loaded into your context.
-- `memory/HISTORY.md` — Append-only event log. NOT loaded into context. Search it with grep. Each entry starts with [YYYY-MM-DD HH:MM].
+- `memory/HISTORY.md` — Append-only event log. NOT loaded into context. Search it with grep-style tools or in-memory filters. Each entry starts with [YYYY-MM-DD HH:MM].
 
 ## Search Past Events
 
-```bash
+Choose the search method based on file size:
-grep -i "keyword" memory/HISTORY.md
-```
 
-Use the `exec` tool to run grep. Combine patterns: `grep -iE "meeting|deadline" memory/HISTORY.md`
+- Small `memory/HISTORY.md`: use `read_file`, then search in-memory
+- Large or long-lived `memory/HISTORY.md`: use the `exec` tool for targeted search
+
+Examples:
+- **Linux/macOS:** `grep -i "keyword" memory/HISTORY.md`
+- **Windows:** `findstr /i "keyword" memory\HISTORY.md`
+- **Cross-platform Python:** `python -c "from pathlib import Path; text = Path('memory/HISTORY.md').read_text(encoding='utf-8'); print('\n'.join([l for l in text.splitlines() if 'keyword' in l.lower()][-20:]))"`
+
+Prefer targeted command-line search for large history files.
 
 ## When to Update MEMORY.md
 

nanobot/skills/skill-creator/SKILL.md

@@ -268,6 +268,8 @@ Skip this step only if the skill being developed already exists, and iteration o
 
 When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
 
+For `nanobot`, custom skills should live under the active workspace `skills/` directory so they can be discovered automatically at runtime (for example, `<workspace>/skills/my-skill/SKILL.md`).
+
 Usage:
 
 ```bash
@@ -277,9 +279,9 @@ scripts/init_skill.py <skill-name> --path <output-directory> [--resources script
 Examples:
 
 ```bash
-scripts/init_skill.py my-skill --path skills/public
+scripts/init_skill.py my-skill --path ./workspace/skills
-scripts/init_skill.py my-skill --path skills/public --resources scripts,references
+scripts/init_skill.py my-skill --path ./workspace/skills --resources scripts,references
-scripts/init_skill.py my-skill --path skills/public --resources scripts --examples
+scripts/init_skill.py my-skill --path ./workspace/skills --resources scripts --examples
 ```
 
 The script:
@@ -326,7 +328,7 @@ Write the YAML frontmatter with `name` and `description`:
   - Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to the agent.
   - Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when the agent needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
 
-Do not include any other fields in YAML frontmatter.
+Keep frontmatter minimal. In `nanobot`, `metadata` and `always` are also supported when needed, but avoid adding extra fields unless they are actually required.
 
 ##### Body
 
@@ -349,7 +351,6 @@ scripts/package_skill.py <path/to/skill-folder> ./dist
 The packaging script will:
 
 1. **Validate** the skill automatically, checking:
-
    - YAML frontmatter format and required fields
    - Skill naming conventions and directory structure
    - Description completeness and quality
@@ -357,6 +358,8 @@ The packaging script will:
 
 2. **Package** the skill if validation passes, creating a .skill file named after the skill (e.g., `my-skill.skill`) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension.
 
+   Security restriction: symlinks are rejected and packaging fails when any symlink is present.
+
 If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again.
 
 ### Step 6: Iterate

nanobot/skills/skill-creator/scripts/init_skill.py

@@ -0,0 +1,378 @@
+#!/usr/bin/env python3
+"""
+Skill Initializer - Creates a new skill from template
+
+Usage:
+    init_skill.py <skill-name> --path <path> [--resources scripts,references,assets] [--examples]
+
+Examples:
+    init_skill.py my-new-skill --path skills/public
+    init_skill.py my-new-skill --path skills/public --resources scripts,references
+    init_skill.py my-api-helper --path skills/private --resources scripts --examples
+    init_skill.py custom-skill --path /custom/location
+"""
+
+import argparse
+import re
+import sys
+from pathlib import Path
+
+MAX_SKILL_NAME_LENGTH = 64
+ALLOWED_RESOURCES = {"scripts", "references", "assets"}
+
+SKILL_TEMPLATE = """---
+name: {skill_name}
+description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
+---
+
+# {skill_title}
+
+## Overview
+
+[TODO: 1-2 sentences explaining what this skill enables]
+
+## Structuring This Skill
+
+[TODO: Choose the structure that best fits this skill's purpose. Common patterns:
+
+**1. Workflow-Based** (best for sequential processes)
+- Works well when there are clear step-by-step procedures
+- Example: DOCX skill with "Workflow Decision Tree" -> "Reading" -> "Creating" -> "Editing"
+- Structure: ## Overview -> ## Workflow Decision Tree -> ## Step 1 -> ## Step 2...
+
+**2. Task-Based** (best for tool collections)
+- Works well when the skill offers different operations/capabilities
+- Example: PDF skill with "Quick Start" -> "Merge PDFs" -> "Split PDFs" -> "Extract Text"
+- Structure: ## Overview -> ## Quick Start -> ## Task Category 1 -> ## Task Category 2...
+
+**3. Reference/Guidelines** (best for standards or specifications)
+- Works well for brand guidelines, coding standards, or requirements
+- Example: Brand styling with "Brand Guidelines" -> "Colors" -> "Typography" -> "Features"
+- Structure: ## Overview -> ## Guidelines -> ## Specifications -> ## Usage...
+
+**4. Capabilities-Based** (best for integrated systems)
+- Works well when the skill provides multiple interrelated features
+- Example: Product Management with "Core Capabilities" -> numbered capability list
+- Structure: ## Overview -> ## Core Capabilities -> ### 1. Feature -> ### 2. Feature...
+
+Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).
+
+Delete this entire "Structuring This Skill" section when done - it's just guidance.]
+
+## [TODO: Replace with the first main section based on chosen structure]
+
+[TODO: Add content here. See examples in existing skills:
+- Code samples for technical skills
+- Decision trees for complex workflows
+- Concrete examples with realistic user requests
+- References to scripts/templates/references as needed]
+
+## Resources (optional)
+
+Create only the resource directories this skill actually needs. Delete this section if no resources are required.
+
+### scripts/
+Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.
+
+**Examples from other skills:**
+- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
+- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing
+
+**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.
+
+**Note:** Scripts may be executed without loading into context, but can still be read by Codex for patching or environment adjustments.
+
+### references/
+Documentation and reference material intended to be loaded into context to inform Codex's process and thinking.
+
+**Examples from other skills:**
+- Product management: `communication.md`, `context_building.md` - detailed workflow guides
+- BigQuery: API reference documentation and query examples
+- Finance: Schema documentation, company policies
+
+**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working.
+
+### assets/
+Files not intended to be loaded into context, but rather used within the output Codex produces.
+
+**Examples from other skills:**
+- Brand styling: PowerPoint template files (.pptx), logo files
+- Frontend builder: HTML/React boilerplate project directories
+- Typography: Font files (.ttf, .woff2)
+
+**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.
+
+---
+
+**Not every skill requires all three types of resources.**
+"""
+
+EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
+"""
+Example helper script for {skill_name}
+
+This is a placeholder script that can be executed directly.
+Replace with actual implementation or delete if not needed.
+
+Example real scripts from other skills:
+- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
+- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
+"""
+
+def main():
+    print("This is an example script for {skill_name}")
+    # TODO: Add actual script logic here
+    # This could be data processing, file conversion, API calls, etc.
+
+if __name__ == "__main__":
+    main()
+'''
+
+EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}
+
+This is a placeholder for detailed reference documentation.
+Replace with actual reference content or delete if not needed.
+
+Example real reference docs from other skills:
+- product-management/references/communication.md - Comprehensive guide for status updates
+- product-management/references/context_building.md - Deep-dive on gathering context
+- bigquery/references/ - API references and query examples
+
+## When Reference Docs Are Useful
+
+Reference docs are ideal for:
+- Comprehensive API documentation
+- Detailed workflow guides
+- Complex multi-step processes
+- Information too lengthy for main SKILL.md
+- Content that's only needed for specific use cases
+
+## Structure Suggestions
+
+### API Reference Example
+- Overview
+- Authentication
+- Endpoints with examples
+- Error codes
+- Rate limits
+
+### Workflow Guide Example
+- Prerequisites
+- Step-by-step instructions
+- Common patterns
+- Troubleshooting
+- Best practices
+"""
+
+EXAMPLE_ASSET = """# Example Asset File
+
+This placeholder represents where asset files would be stored.
+Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.
+
+Asset files are NOT intended to be loaded into context, but rather used within
+the output Codex produces.
+
+Example asset files from other skills:
+- Brand guidelines: logo.png, slides_template.pptx
+- Frontend builder: hello-world/ directory with HTML/React boilerplate
+- Typography: custom-font.ttf, font-family.woff2
+- Data: sample_data.csv, test_dataset.json
+
+## Common Asset Types
+
+- Templates: .pptx, .docx, boilerplate directories
+- Images: .png, .jpg, .svg, .gif
+- Fonts: .ttf, .otf, .woff, .woff2
+- Boilerplate code: Project directories, starter files
+- Icons: .ico, .svg
+- Data files: .csv, .json, .xml, .yaml
+
+Note: This is a text placeholder. Actual assets can be any file type.
+"""
+
+
+def normalize_skill_name(skill_name):
+    """Normalize a skill name to lowercase hyphen-case."""
+    normalized = skill_name.strip().lower()
+    normalized = re.sub(r"[^a-z0-9]+", "-", normalized)
+    normalized = normalized.strip("-")
+    normalized = re.sub(r"-{2,}", "-", normalized)
+    return normalized
+
+
+def title_case_skill_name(skill_name):
+    """Convert hyphenated skill name to Title Case for display."""
+    return " ".join(word.capitalize() for word in skill_name.split("-"))
+
+
+def parse_resources(raw_resources):
+    if not raw_resources:
+        return []
+    resources = [item.strip() for item in raw_resources.split(",") if item.strip()]
+    invalid = sorted({item for item in resources if item not in ALLOWED_RESOURCES})
+    if invalid:
+        allowed = ", ".join(sorted(ALLOWED_RESOURCES))
+        print(f"[ERROR] Unknown resource type(s): {', '.join(invalid)}")
+        print(f"   Allowed: {allowed}")
+        sys.exit(1)
+    deduped = []
+    seen = set()
+    for resource in resources:
+        if resource not in seen:
+            deduped.append(resource)
+            seen.add(resource)
+    return deduped
+
+
+def create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples):
+    for resource in resources:
+        resource_dir = skill_dir / resource
+        resource_dir.mkdir(exist_ok=True)
+        if resource == "scripts":
+            if include_examples:
+                example_script = resource_dir / "example.py"
+                example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
+                example_script.chmod(0o755)
+                print("[OK] Created scripts/example.py")
+            else:
+                print("[OK] Created scripts/")
+        elif resource == "references":
+            if include_examples:
+                example_reference = resource_dir / "api_reference.md"
+                example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
+                print("[OK] Created references/api_reference.md")
+            else:
+                print("[OK] Created references/")
+        elif resource == "assets":
+            if include_examples:
+                example_asset = resource_dir / "example_asset.txt"
+                example_asset.write_text(EXAMPLE_ASSET)
+                print("[OK] Created assets/example_asset.txt")
+            else:
+                print("[OK] Created assets/")
+
+
+def init_skill(skill_name, path, resources, include_examples):
+    """
+    Initialize a new skill directory with template SKILL.md.
+
+    Args:
+        skill_name: Name of the skill
+        path: Path where the skill directory should be created
+        resources: Resource directories to create
+        include_examples: Whether to create example files in resource directories
+
+    Returns:
+        Path to created skill directory, or None if error
+    """
+    # Determine skill directory path
+    skill_dir = Path(path).resolve() / skill_name
+
+    # Check if directory already exists
+    if skill_dir.exists():
+        print(f"[ERROR] Skill directory already exists: {skill_dir}")
+        return None
+
+    # Create skill directory
+    try:
+        skill_dir.mkdir(parents=True, exist_ok=False)
+        print(f"[OK] Created skill directory: {skill_dir}")
+    except Exception as e:
+        print(f"[ERROR] Error creating directory: {e}")
+        return None
+
+    # Create SKILL.md from template
+    skill_title = title_case_skill_name(skill_name)
+    skill_content = SKILL_TEMPLATE.format(skill_name=skill_name, skill_title=skill_title)
+
+    skill_md_path = skill_dir / "SKILL.md"
+    try:
+        skill_md_path.write_text(skill_content)
+        print("[OK] Created SKILL.md")
+    except Exception as e:
+        print(f"[ERROR] Error creating SKILL.md: {e}")
+        return None
+
+    # Create resource directories if requested
+    if resources:
+        try:
+            create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples)
+        except Exception as e:
+            print(f"[ERROR] Error creating resource directories: {e}")
+            return None
+
+    # Print next steps
+    print(f"\n[OK] Skill '{skill_name}' initialized successfully at {skill_dir}")
+    print("\nNext steps:")
+    print("1. Edit SKILL.md to complete the TODO items and update the description")
+    if resources:
+        if include_examples:
+            print("2. Customize or delete the example files in scripts/, references/, and assets/")
+        else:
+            print("2. Add resources to scripts/, references/, and assets/ as needed")
+    else:
+        print("2. Create resource directories only if needed (scripts/, references/, assets/)")
+    print("3. Run the validator when ready to check the skill structure")
+
+    return skill_dir
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Create a new skill directory with a SKILL.md template.",
+    )
+    parser.add_argument("skill_name", help="Skill name (normalized to hyphen-case)")
+    parser.add_argument("--path", required=True, help="Output directory for the skill")
+    parser.add_argument(
+        "--resources",
+        default="",
+        help="Comma-separated list: scripts,references,assets",
+    )
+    parser.add_argument(
+        "--examples",
+        action="store_true",
+        help="Create example files inside the selected resource directories",
+    )
+    args = parser.parse_args()
+
+    raw_skill_name = args.skill_name
+    skill_name = normalize_skill_name(raw_skill_name)
+    if not skill_name:
+        print("[ERROR] Skill name must include at least one letter or digit.")
+        sys.exit(1)
+    if len(skill_name) > MAX_SKILL_NAME_LENGTH:
+        print(
+            f"[ERROR] Skill name '{skill_name}' is too long ({len(skill_name)} characters). "
+            f"Maximum is {MAX_SKILL_NAME_LENGTH} characters."
+        )
+        sys.exit(1)
+    if skill_name != raw_skill_name:
+        print(f"Note: Normalized skill name from '{raw_skill_name}' to '{skill_name}'.")
+
+    resources = parse_resources(args.resources)
+    if args.examples and not resources:
+        print("[ERROR] --examples requires --resources to be set.")
+        sys.exit(1)
+
+    path = args.path
+
+    print(f"Initializing skill: {skill_name}")
+    print(f"   Location: {path}")
+    if resources:
+        print(f"   Resources: {', '.join(resources)}")
+        if args.examples:
+            print("   Examples: enabled")
+    else:
+        print("   Resources: none (create as needed)")
+    print()
+
+    result = init_skill(skill_name, path, resources, args.examples)
+
+    if result:
+        sys.exit(0)
+    else:
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

nanobot/skills/skill-creator/scripts/package_skill.py

@@ -0,0 +1,154 @@
+#!/usr/bin/env python3
+"""
+Skill Packager - Creates a distributable .skill file of a skill folder
+
+Usage:
+    python package_skill.py <path/to/skill-folder> [output-directory]
+
+Example:
+    python package_skill.py skills/public/my-skill
+    python package_skill.py skills/public/my-skill ./dist
+"""
+
+import sys
+import zipfile
+from pathlib import Path
+
+from quick_validate import validate_skill
+
+
+def _is_within(path: Path, root: Path) -> bool:
+    try:
+        path.relative_to(root)
+        return True
+    except ValueError:
+        return False
+
+
+def _cleanup_partial_archive(skill_filename: Path) -> None:
+    try:
+        if skill_filename.exists():
+            skill_filename.unlink()
+    except OSError:
+        pass
+
+
+def package_skill(skill_path, output_dir=None):
+    """
+    Package a skill folder into a .skill file.
+
+    Args:
+        skill_path: Path to the skill folder
+        output_dir: Optional output directory for the .skill file (defaults to current directory)
+
+    Returns:
+        Path to the created .skill file, or None if error
+    """
+    skill_path = Path(skill_path).resolve()
+
+    # Validate skill folder exists
+    if not skill_path.exists():
+        print(f"[ERROR] Skill folder not found: {skill_path}")
+        return None
+
+    if not skill_path.is_dir():
+        print(f"[ERROR] Path is not a directory: {skill_path}")
+        return None
+
+    # Validate SKILL.md exists
+    skill_md = skill_path / "SKILL.md"
+    if not skill_md.exists():
+        print(f"[ERROR] SKILL.md not found in {skill_path}")
+        return None
+
+    # Run validation before packaging
+    print("Validating skill...")
+    valid, message = validate_skill(skill_path)
+    if not valid:
+        print(f"[ERROR] Validation failed: {message}")
+        print("   Please fix the validation errors before packaging.")
+        return None
+    print(f"[OK] {message}\n")
+
+    # Determine output location
+    skill_name = skill_path.name
+    if output_dir:
+        output_path = Path(output_dir).resolve()
+        output_path.mkdir(parents=True, exist_ok=True)
+    else:
+        output_path = Path.cwd()
+
+    skill_filename = output_path / f"{skill_name}.skill"
+
+    EXCLUDED_DIRS = {".git", ".svn", ".hg", "__pycache__", "node_modules"}
+
+    files_to_package = []
+    resolved_archive = skill_filename.resolve()
+
+    for file_path in skill_path.rglob("*"):
+        # Fail closed on symlinks so the packaged contents are explicit and predictable.
+        if file_path.is_symlink():
+            print(f"[ERROR] Symlink not allowed in packaged skill: {file_path}")
+            _cleanup_partial_archive(skill_filename)
+            return None
+
+        rel_parts = file_path.relative_to(skill_path).parts
+        if any(part in EXCLUDED_DIRS for part in rel_parts):
+            continue
+
+        if file_path.is_file():
+            resolved_file = file_path.resolve()
+            if not _is_within(resolved_file, skill_path):
+                print(f"[ERROR] File escapes skill root: {file_path}")
+                _cleanup_partial_archive(skill_filename)
+                return None
+            # If output lives under skill_path, avoid writing archive into itself.
+            if resolved_file == resolved_archive:
+                print(f"[WARN] Skipping output archive: {file_path}")
+                continue
+            files_to_package.append(file_path)
+
+    # Create the .skill file (zip format)
+    try:
+        with zipfile.ZipFile(skill_filename, "w", zipfile.ZIP_DEFLATED) as zipf:
+            for file_path in files_to_package:
+                # Calculate the relative path within the zip.
+                arcname = Path(skill_name) / file_path.relative_to(skill_path)
+                zipf.write(file_path, arcname)
+                print(f"  Added: {arcname}")
+
+        print(f"\n[OK] Successfully packaged skill to: {skill_filename}")
+        return skill_filename
+
+    except Exception as e:
+        _cleanup_partial_archive(skill_filename)
+        print(f"[ERROR] Error creating .skill file: {e}")
+        return None
+
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: python package_skill.py <path/to/skill-folder> [output-directory]")
+        print("\nExample:")
+        print("  python package_skill.py skills/public/my-skill")
+        print("  python package_skill.py skills/public/my-skill ./dist")
+        sys.exit(1)
+
+    skill_path = sys.argv[1]
+    output_dir = sys.argv[2] if len(sys.argv) > 2 else None
+
+    print(f"Packaging skill: {skill_path}")
+    if output_dir:
+        print(f"   Output directory: {output_dir}")
+    print()
+
+    result = package_skill(skill_path, output_dir)
+
+    if result:
+        sys.exit(0)
+    else:
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

nanobot/skills/skill-creator/scripts/quick_validate.py

@@ -0,0 +1,213 @@
+#!/usr/bin/env python3
+"""
+Minimal validator for nanobot skill folders.
+"""
+
+import re
+import sys
+from pathlib import Path
+from typing import Optional
+
+try:
+    import yaml
+except ModuleNotFoundError:
+    yaml = None
+
+MAX_SKILL_NAME_LENGTH = 64
+ALLOWED_FRONTMATTER_KEYS = {
+    "name",
+    "description",
+    "metadata",
+    "always",
+    "license",
+    "allowed-tools",
+}
+ALLOWED_RESOURCE_DIRS = {"scripts", "references", "assets"}
+PLACEHOLDER_MARKERS = ("[todo", "todo:")
+
+
+def _extract_frontmatter(content: str) -> Optional[str]:
+    lines = content.splitlines()
+    if not lines or lines[0].strip() != "---":
+        return None
+    for i in range(1, len(lines)):
+        if lines[i].strip() == "---":
+            return "\n".join(lines[1:i])
+    return None
+
+
+def _parse_simple_frontmatter(frontmatter_text: str) -> Optional[dict[str, str]]:
+    """Fallback parser for simple frontmatter when PyYAML is unavailable."""
+    parsed: dict[str, str] = {}
+    current_key: Optional[str] = None
+    multiline_key: Optional[str] = None
+
+    for raw_line in frontmatter_text.splitlines():
+        stripped = raw_line.strip()
+        if not stripped or stripped.startswith("#"):
+            continue
+
+        is_indented = raw_line[:1].isspace()
+        if is_indented:
+            if current_key is None:
+                return None
+            current_value = parsed[current_key]
+            parsed[current_key] = f"{current_value}\n{stripped}" if current_value else stripped
+            continue
+
+        if ":" not in stripped:
+            return None
+
+        key, value = stripped.split(":", 1)
+        key = key.strip()
+        value = value.strip()
+        if not key:
+            return None
+
+        if value in {"|", ">"}:
+            parsed[key] = ""
+            current_key = key
+            multiline_key = key
+            continue
+
+        if (value.startswith('"') and value.endswith('"')) or (
+            value.startswith("'") and value.endswith("'")
+        ):
+            value = value[1:-1]
+        parsed[key] = value
+        current_key = key
+        multiline_key = None
+
+    if multiline_key is not None and multiline_key not in parsed:
+        return None
+    return parsed
+
+
+def _load_frontmatter(frontmatter_text: str) -> tuple[Optional[dict], Optional[str]]:
+    if yaml is not None:
+        try:
+            frontmatter = yaml.safe_load(frontmatter_text)
+        except yaml.YAMLError as exc:
+            return None, f"Invalid YAML in frontmatter: {exc}"
+        if not isinstance(frontmatter, dict):
+            return None, "Frontmatter must be a YAML dictionary"
+        return frontmatter, None
+
+    frontmatter = _parse_simple_frontmatter(frontmatter_text)
+    if frontmatter is None:
+        return None, "Invalid YAML in frontmatter: unsupported syntax without PyYAML installed"
+    return frontmatter, None
+
+
+def _validate_skill_name(name: str, folder_name: str) -> Optional[str]:
+    if not re.fullmatch(r"[a-z0-9]+(?:-[a-z0-9]+)*", name):
+        return (
+            f"Name '{name}' should be hyphen-case "
+            "(lowercase letters, digits, and single hyphens only)"
+        )
+    if len(name) > MAX_SKILL_NAME_LENGTH:
+        return (
+            f"Name is too long ({len(name)} characters). "
+            f"Maximum is {MAX_SKILL_NAME_LENGTH} characters."
+        )
+    if name != folder_name:
+        return f"Skill name '{name}' must match directory name '{folder_name}'"
+    return None
+
+
+def _validate_description(description: str) -> Optional[str]:
+    trimmed = description.strip()
+    if not trimmed:
+        return "Description cannot be empty"
+    lowered = trimmed.lower()
+    if any(marker in lowered for marker in PLACEHOLDER_MARKERS):
+        return "Description still contains TODO placeholder text"
+    if "<" in trimmed or ">" in trimmed:
+        return "Description cannot contain angle brackets (< or >)"
+    if len(trimmed) > 1024:
+        return f"Description is too long ({len(trimmed)} characters). Maximum is 1024 characters."
+    return None
+
+
+def validate_skill(skill_path):
+    """Validate a skill folder structure and required frontmatter."""
+    skill_path = Path(skill_path).resolve()
+
+    if not skill_path.exists():
+        return False, f"Skill folder not found: {skill_path}"
+    if not skill_path.is_dir():
+        return False, f"Path is not a directory: {skill_path}"
+
+    skill_md = skill_path / "SKILL.md"
+    if not skill_md.exists():
+        return False, "SKILL.md not found"
+
+    try:
+        content = skill_md.read_text(encoding="utf-8")
+    except OSError as exc:
+        return False, f"Could not read SKILL.md: {exc}"
+
+    frontmatter_text = _extract_frontmatter(content)
+    if frontmatter_text is None:
+        return False, "Invalid frontmatter format"
+
+    frontmatter, error = _load_frontmatter(frontmatter_text)
+    if error:
+        return False, error
+
+    unexpected_keys = sorted(set(frontmatter.keys()) - ALLOWED_FRONTMATTER_KEYS)
+    if unexpected_keys:
+        allowed = ", ".join(sorted(ALLOWED_FRONTMATTER_KEYS))
+        unexpected = ", ".join(unexpected_keys)
+        return (
+            False,
+            f"Unexpected key(s) in SKILL.md frontmatter: {unexpected}. Allowed properties are: {allowed}",
+        )
+
+    if "name" not in frontmatter:
+        return False, "Missing 'name' in frontmatter"
+    if "description" not in frontmatter:
+        return False, "Missing 'description' in frontmatter"
+
+    name = frontmatter["name"]
+    if not isinstance(name, str):
+        return False, f"Name must be a string, got {type(name).__name__}"
+    name_error = _validate_skill_name(name.strip(), skill_path.name)
+    if name_error:
+        return False, name_error
+
+    description = frontmatter["description"]
+    if not isinstance(description, str):
+        return False, f"Description must be a string, got {type(description).__name__}"
+    description_error = _validate_description(description)
+    if description_error:
+        return False, description_error
+
+    always = frontmatter.get("always")
+    if always is not None and not isinstance(always, bool):
+        return False, f"'always' must be a boolean, got {type(always).__name__}"
+
+    for child in skill_path.iterdir():
+        if child.name == "SKILL.md":
+            continue
+        if child.is_dir() and child.name in ALLOWED_RESOURCE_DIRS:
+            continue
+        if child.is_symlink():
+            continue
+        return (
+            False,
+            f"Unexpected file or directory in skill root: {child.name}. "
+            "Only SKILL.md, scripts/, references/, and assets/ are allowed.",
+        )
+
+    return True, "Skill is valid!"
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python quick_validate.py <skill_directory>")
+        sys.exit(1)
+
+    valid, message = validate_skill(sys.argv[1])
+    print(message)
+    sys.exit(0 if valid else 1)

nanobot/templates/AGENTS.md

@@ -4,17 +4,15 @@ You are a helpful AI assistant. Be concise, accurate, and friendly.
 
 ## Scheduled Reminders
 
-When user asks for a reminder at a specific time, use `exec` to run:
+Before scheduling reminders, check available skills and follow skill guidance first.
-```
+Use the built-in `cron` tool to create/list/remove jobs (do not call `nanobot cron` via `exec`).
-nanobot cron add --name "reminder" --message "Your message" --at "YYYY-MM-DDTHH:MM:SS" --deliver --to "USER_ID" --channel "CHANNEL"
-```
 Get USER_ID and CHANNEL from the current session (e.g., `8281248569` and `telegram` from `telegram:8281248569`).
 
 **Do NOT just write reminders to MEMORY.md** — that won't trigger actual notifications.
 
 ## Heartbeat Tasks
 
-`HEARTBEAT.md` is checked every 30 minutes. Use file tools to manage periodic tasks:
+`HEARTBEAT.md` is checked on the configured heartbeat interval. Use file tools to manage periodic tasks:
 
 - **Add**: `edit_file` to append new tasks
 - **Remove**: `edit_file` to delete completed tasks

nanobot/utils/__init__.py

@@ -1,5 +1,5 @@
 """Utility functions for nanobot."""
 
-from nanobot.utils.helpers import ensure_dir, get_data_path, get_workspace_path
+from nanobot.utils.helpers import ensure_dir
 
-__all__ = ["ensure_dir", "get_workspace_path", "get_data_path"]
+__all__ = ["ensure_dir"]

nanobot/utils/helpers.py

@@ -1,8 +1,25 @@
 """Utility functions for nanobot."""
 
+import json
 import re
 from datetime import datetime
 from pathlib import Path
+from typing import Any
+
+import tiktoken
+
+
+def detect_image_mime(data: bytes) -> str | None:
+    """Detect image MIME type from magic bytes, ignoring file extension."""
+    if data[:8] == b"\x89PNG\r\n\x1a\n":
+        return "image/png"
+    if data[:3] == b"\xff\xd8\xff":
+        return "image/jpeg"
+    if data[:6] in (b"GIF87a", b"GIF89a"):
+        return "image/gif"
+    if data[:4] == b"RIFF" and data[8:12] == b"WEBP":
+        return "image/webp"
+    return None
 
 
 def ensure_dir(path: Path) -> Path:
@@ -11,17 +28,6 @@ def ensure_dir(path: Path) -> Path:
     return path
 
 
-def get_data_path() -> Path:
-    """~/.nanobot data directory."""
-    return ensure_dir(Path.home() / ".nanobot")
-
-
-def get_workspace_path(workspace: str | None = None) -> Path:
-    """Resolve and ensure workspace path. Defaults to ~/.nanobot/workspace."""
-    path = Path(workspace).expanduser() if workspace else Path.home() / ".nanobot" / "workspace"
-    return ensure_dir(path)
-
-
 def timestamp() -> str:
     """Current ISO timestamp."""
     return datetime.now().isoformat()
@@ -34,6 +40,136 @@ def safe_filename(name: str) -> str:
     return _UNSAFE_CHARS.sub("_", name).strip()
 
 
+def split_message(content: str, max_len: int = 2000) -> list[str]:
+    """
+    Split content into chunks within max_len, preferring line breaks.
+
+    Args:
+        content: The text content to split.
+        max_len: Maximum length per chunk (default 2000 for Discord compatibility).
+
+    Returns:
+        List of message chunks, each within max_len.
+    """
+    if not content:
+        return []
+    if len(content) <= max_len:
+        return [content]
+    chunks: list[str] = []
+    while content:
+        if len(content) <= max_len:
+            chunks.append(content)
+            break
+        cut = content[:max_len]
+        # Try to break at newline first, then space, then hard break
+        pos = cut.rfind('\n')
+        if pos <= 0:
+            pos = cut.rfind(' ')
+        if pos <= 0:
+            pos = max_len
+        chunks.append(content[:pos])
+        content = content[pos:].lstrip()
+    return chunks
+
+
+def build_assistant_message(
+    content: str | None,
+    tool_calls: list[dict[str, Any]] | None = None,
+    reasoning_content: str | None = None,
+    thinking_blocks: list[dict] | None = None,
+) -> dict[str, Any]:
+    """Build a provider-safe assistant message with optional reasoning fields."""
+    msg: dict[str, Any] = {"role": "assistant", "content": content}
+    if tool_calls:
+        msg["tool_calls"] = tool_calls
+    if reasoning_content is not None:
+        msg["reasoning_content"] = reasoning_content
+    if thinking_blocks:
+        msg["thinking_blocks"] = thinking_blocks
+    return msg
+
+
+def estimate_prompt_tokens(
+    messages: list[dict[str, Any]],
+    tools: list[dict[str, Any]] | None = None,
+) -> int:
+    """Estimate prompt tokens with tiktoken."""
+    try:
+        enc = tiktoken.get_encoding("cl100k_base")
+        parts: list[str] = []
+        for msg in messages:
+            content = msg.get("content")
+            if isinstance(content, str):
+                parts.append(content)
+            elif isinstance(content, list):
+                for part in content:
+                    if isinstance(part, dict) and part.get("type") == "text":
+                        txt = part.get("text", "")
+                        if txt:
+                            parts.append(txt)
+        if tools:
+            parts.append(json.dumps(tools, ensure_ascii=False))
+        return len(enc.encode("\n".join(parts)))
+    except Exception:
+        return 0
+
+
+def estimate_message_tokens(message: dict[str, Any]) -> int:
+    """Estimate prompt tokens contributed by one persisted message."""
+    content = message.get("content")
+    parts: list[str] = []
+    if isinstance(content, str):
+        parts.append(content)
+    elif isinstance(content, list):
+        for part in content:
+            if isinstance(part, dict) and part.get("type") == "text":
+                text = part.get("text", "")
+                if text:
+                    parts.append(text)
+            else:
+                parts.append(json.dumps(part, ensure_ascii=False))
+    elif content is not None:
+        parts.append(json.dumps(content, ensure_ascii=False))
+
+    for key in ("name", "tool_call_id"):
+        value = message.get(key)
+        if isinstance(value, str) and value:
+            parts.append(value)
+    if message.get("tool_calls"):
+        parts.append(json.dumps(message["tool_calls"], ensure_ascii=False))
+
+    payload = "\n".join(parts)
+    if not payload:
+        return 1
+    try:
+        enc = tiktoken.get_encoding("cl100k_base")
+        return max(1, len(enc.encode(payload)))
+    except Exception:
+        return max(1, len(payload) // 4)
+
+
+def estimate_prompt_tokens_chain(
+    provider: Any,
+    model: str | None,
+    messages: list[dict[str, Any]],
+    tools: list[dict[str, Any]] | None = None,
+) -> tuple[int, str]:
+    """Estimate prompt tokens via provider counter first, then tiktoken fallback."""
+    provider_counter = getattr(provider, "estimate_prompt_tokens", None)
+    if callable(provider_counter):
+        try:
+            tokens, source = provider_counter(messages, tools, model)
+            if isinstance(tokens, (int, float)) and tokens > 0:
+                return int(tokens), str(source or "provider_counter")
+        except Exception:
+            pass
+
+    estimated = estimate_prompt_tokens(messages, tools)
+    if estimated > 0:
+        return int(estimated), "tiktoken"
+    return 0, "none"
+
+
 def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]:
     """Sync bundled templates to workspace. Only creates missing files."""
     from importlib.resources import files as pkg_files
@@ -54,7 +190,7 @@ def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]
         added.append(str(dest.relative_to(workspace)))
 
     for item in tpl.iterdir():
-        if item.name.endswith(".md"):
+        if item.name.endswith(".md") and not item.name.startswith("."):
             _write(item, workspace / item.name)
     _write(tpl / "memory" / "MEMORY.md", workspace / "memory" / "MEMORY.md")
     _write(None, workspace / "memory" / "HISTORY.md")

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "nanobot-ai"
-version = "0.1.4.post3"
+version = "0.1.4.post4"
 description = "A lightweight personal AI assistant framework"
 requires-python = ">=3.11"
 license = {text = "MIT"}
@@ -18,7 +18,7 @@ classifiers = [
 
 dependencies = [
     "typer>=0.20.0,<1.0.0",
-    "litellm>=1.81.5,<2.0.0",
+    "litellm>=1.82.1,<2.0.0",
     "pydantic>=2.12.0,<3.0.0",
     "pydantic-settings>=2.12.0,<3.0.0",
     "websockets>=16.0,<17.0",
@@ -30,7 +30,7 @@ dependencies = [
     "rich>=14.0.0,<15.0.0",
     "croniter>=6.0.0,<7.0.0",
     "dingtalk-stream>=0.24.0,<1.0.0",
-    "python-telegram-bot[socks]>=22.0,<23.0",
+    "python-telegram-bot[socks]>=22.6,<23.0",
     "lark-oapi>=1.5.0,<2.0.0",
     "socksio>=1.0.0,<2.0.0",
     "python-socketio>=5.16.0,<6.0.0",
@@ -42,9 +42,15 @@ dependencies = [
     "prompt-toolkit>=3.0.50,<4.0.0",
     "mcp>=1.26.0,<2.0.0",
     "json-repair>=0.57.0,<1.0.0",
+    "chardet>=3.0.2,<6.0.0",
+    "openai>=2.8.0",
+    "tiktoken>=0.12.0,<1.0.0",
 ]
 
 [project.optional-dependencies]
+wecom = [
+    "wecom-aibot-sdk-python @ git+https://github.com/chengyongru/wecom_aibot_sdk.git@v0.1.2",
+]
 matrix = [
     "matrix-nio[e2e]>=0.25.2",
     "mistune>=3.0.0,<4.0.0",
@@ -54,6 +60,9 @@ dev = [
     "pytest>=9.0.0,<10.0.0",
     "pytest-asyncio>=1.3.0,<2.0.0",
     "ruff>=0.1.0",
+    "matrix-nio[e2e]>=0.25.2",
+    "mistune>=3.0.0,<4.0.0",
+    "nh3>=0.2.17,<1.0.0",
 ]
 
 [project.scripts]
@@ -63,6 +72,9 @@ nanobot = "nanobot.cli.commands:app"
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
+[tool.hatch.metadata]
+allow-direct-references = true
+
 [tool.hatch.build.targets.wheel]
 packages = ["nanobot"]
 

tests/test_azure_openai_provider.py

@@ -0,0 +1,399 @@
+"""Test Azure OpenAI provider implementation (updated for model-based deployment names)."""
+
+from unittest.mock import AsyncMock, Mock, patch
+
+import pytest
+
+from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
+from nanobot.providers.base import LLMResponse
+
+
+def test_azure_openai_provider_init():
+    """Test AzureOpenAIProvider initialization without deployment_name."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o-deployment",
+    )
+    
+    assert provider.api_key == "test-key"
+    assert provider.api_base == "https://test-resource.openai.azure.com/"
+    assert provider.default_model == "gpt-4o-deployment"
+    assert provider.api_version == "2024-10-21"
+
+
+def test_azure_openai_provider_init_validation():
+    """Test AzureOpenAIProvider initialization validation."""
+    # Missing api_key
+    with pytest.raises(ValueError, match="Azure OpenAI api_key is required"):
+        AzureOpenAIProvider(api_key="", api_base="https://test.com")
+    
+    # Missing api_base
+    with pytest.raises(ValueError, match="Azure OpenAI api_base is required"):
+        AzureOpenAIProvider(api_key="test", api_base="")
+
+
+def test_build_chat_url():
+    """Test Azure OpenAI URL building with different deployment names."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    # Test various deployment names
+    test_cases = [
+        ("gpt-4o-deployment", "https://test-resource.openai.azure.com/openai/deployments/gpt-4o-deployment/chat/completions?api-version=2024-10-21"),
+        ("gpt-35-turbo", "https://test-resource.openai.azure.com/openai/deployments/gpt-35-turbo/chat/completions?api-version=2024-10-21"),
+        ("custom-model", "https://test-resource.openai.azure.com/openai/deployments/custom-model/chat/completions?api-version=2024-10-21"),
+    ]
+    
+    for deployment_name, expected_url in test_cases:
+        url = provider._build_chat_url(deployment_name)
+        assert url == expected_url
+
+
+def test_build_chat_url_api_base_without_slash():
+    """Test URL building when api_base doesn't end with slash."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",  # No trailing slash
+        default_model="gpt-4o",
+    )
+    
+    url = provider._build_chat_url("test-deployment")
+    expected = "https://test-resource.openai.azure.com/openai/deployments/test-deployment/chat/completions?api-version=2024-10-21"
+    assert url == expected
+
+
+def test_build_headers():
+    """Test Azure OpenAI header building with api-key authentication."""
+    provider = AzureOpenAIProvider(
+        api_key="test-api-key-123",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    headers = provider._build_headers()
+    assert headers["Content-Type"] == "application/json"
+    assert headers["api-key"] == "test-api-key-123"  # Azure OpenAI specific header
+    assert "x-session-affinity" in headers
+
+
+def test_prepare_request_payload():
+    """Test request payload preparation with Azure OpenAI 2024-10-21 compliance."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    messages = [{"role": "user", "content": "Hello"}]
+    payload = provider._prepare_request_payload("gpt-4o", messages, max_tokens=1500, temperature=0.8)
+    
+    assert payload["messages"] == messages
+    assert payload["max_completion_tokens"] == 1500  # Azure API 2024-10-21 uses max_completion_tokens
+    assert payload["temperature"] == 0.8
+    assert "tools" not in payload
+    
+    # Test with tools
+    tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
+    payload_with_tools = provider._prepare_request_payload("gpt-4o", messages, tools=tools)
+    assert payload_with_tools["tools"] == tools
+    assert payload_with_tools["tool_choice"] == "auto"
+    
+    # Test with reasoning_effort
+    payload_with_reasoning = provider._prepare_request_payload(
+        "gpt-5-chat", messages, reasoning_effort="medium"
+    )
+    assert payload_with_reasoning["reasoning_effort"] == "medium"
+    assert "temperature" not in payload_with_reasoning
+
+
+def test_prepare_request_payload_sanitizes_messages():
+    """Test Azure payload strips non-standard message keys before sending."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+
+    messages = [
+        {
+            "role": "assistant",
+            "tool_calls": [{"id": "call_123", "type": "function", "function": {"name": "x"}}],
+            "reasoning_content": "hidden chain-of-thought",
+        },
+        {
+            "role": "tool",
+            "tool_call_id": "call_123",
+            "name": "x",
+            "content": "ok",
+            "extra_field": "should be removed",
+        },
+    ]
+
+    payload = provider._prepare_request_payload("gpt-4o", messages)
+
+    assert payload["messages"] == [
+        {
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "call_123", "type": "function", "function": {"name": "x"}}],
+        },
+        {
+            "role": "tool",
+            "tool_call_id": "call_123",
+            "name": "x",
+            "content": "ok",
+        },
+    ]
+
+
+@pytest.mark.asyncio
+async def test_chat_success():
+    """Test successful chat request using model as deployment name."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o-deployment",
+    )
+    
+    # Mock response data
+    mock_response_data = {
+        "choices": [{
+            "message": {
+                "content": "Hello! How can I help you today?",
+                "role": "assistant"
+            },
+            "finish_reason": "stop"
+        }],
+        "usage": {
+            "prompt_tokens": 12,
+            "completion_tokens": 18,
+            "total_tokens": 30
+        }
+    }
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 200
+        mock_response.json = Mock(return_value=mock_response_data)
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        # Test with specific model (deployment name)
+        messages = [{"role": "user", "content": "Hello"}]
+        result = await provider.chat(messages, model="custom-deployment")
+        
+        assert isinstance(result, LLMResponse)
+        assert result.content == "Hello! How can I help you today?"
+        assert result.finish_reason == "stop"
+        assert result.usage["prompt_tokens"] == 12
+        assert result.usage["completion_tokens"] == 18
+        assert result.usage["total_tokens"] == 30
+        
+        # Verify URL was built with the provided model as deployment name
+        call_args = mock_context.post.call_args
+        expected_url = "https://test-resource.openai.azure.com/openai/deployments/custom-deployment/chat/completions?api-version=2024-10-21"
+        assert call_args[0][0] == expected_url
+
+
+@pytest.mark.asyncio
+async def test_chat_uses_default_model_when_no_model_provided():
+    """Test that chat uses default_model when no model is specified."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="default-deployment",
+    )
+    
+    mock_response_data = {
+        "choices": [{
+            "message": {"content": "Response", "role": "assistant"},
+            "finish_reason": "stop"
+        }],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
+    }
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 200
+        mock_response.json = Mock(return_value=mock_response_data)
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "Test"}]
+        await provider.chat(messages)  # No model specified
+        
+        # Verify URL was built with default model as deployment name
+        call_args = mock_context.post.call_args
+        expected_url = "https://test-resource.openai.azure.com/openai/deployments/default-deployment/chat/completions?api-version=2024-10-21"
+        assert call_args[0][0] == expected_url
+
+
+@pytest.mark.asyncio
+async def test_chat_with_tool_calls():
+    """Test chat request with tool calls in response."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    # Mock response with tool calls
+    mock_response_data = {
+        "choices": [{
+            "message": {
+                "content": None,
+                "role": "assistant",
+                "tool_calls": [{
+                    "id": "call_12345",
+                    "function": {
+                        "name": "get_weather",
+                        "arguments": '{"location": "San Francisco"}'
+                    }
+                }]
+            },
+            "finish_reason": "tool_calls"
+        }],
+        "usage": {
+            "prompt_tokens": 20,
+            "completion_tokens": 15,
+            "total_tokens": 35
+        }
+    }
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 200
+        mock_response.json = Mock(return_value=mock_response_data)
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "What's the weather?"}]
+        tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
+        result = await provider.chat(messages, tools=tools, model="weather-model")
+        
+        assert isinstance(result, LLMResponse)
+        assert result.content is None
+        assert result.finish_reason == "tool_calls"
+        assert len(result.tool_calls) == 1
+        assert result.tool_calls[0].name == "get_weather"
+        assert result.tool_calls[0].arguments == {"location": "San Francisco"}
+
+
+@pytest.mark.asyncio
+async def test_chat_api_error():
+    """Test chat request API error handling."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 401
+        mock_response.text = "Invalid authentication credentials"
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "Hello"}]
+        result = await provider.chat(messages)
+        
+        assert isinstance(result, LLMResponse)
+        assert "Azure OpenAI API Error 401" in result.content
+        assert "Invalid authentication credentials" in result.content
+        assert result.finish_reason == "error"
+
+
+@pytest.mark.asyncio
+async def test_chat_connection_error():
+    """Test chat request connection error handling."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(side_effect=Exception("Connection failed"))
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "Hello"}]
+        result = await provider.chat(messages)
+        
+        assert isinstance(result, LLMResponse)
+        assert "Error calling Azure OpenAI: Exception('Connection failed')" in result.content
+        assert result.finish_reason == "error"
+
+
+def test_parse_response_malformed():
+    """Test response parsing with malformed data."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    # Test with missing choices
+    malformed_response = {"usage": {"prompt_tokens": 10}}
+    result = provider._parse_response(malformed_response)
+    
+    assert isinstance(result, LLMResponse)
+    assert "Error parsing Azure OpenAI response" in result.content
+    assert result.finish_reason == "error"
+
+
+def test_get_default_model():
+    """Test get_default_model method."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="my-custom-deployment",
+    )
+    
+    assert provider.get_default_model() == "my-custom-deployment"
+
+
+if __name__ == "__main__":
+    # Run basic tests
+    print("Running basic Azure OpenAI provider tests...")
+    
+    # Test initialization
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o-deployment",
+    )
+    print("✅ Provider initialization successful")
+    
+    # Test URL building
+    url = provider._build_chat_url("my-deployment")
+    expected = "https://test-resource.openai.azure.com/openai/deployments/my-deployment/chat/completions?api-version=2024-10-21"
+    assert url == expected
+    print("✅ URL building works correctly")
+    
+    # Test headers
+    headers = provider._build_headers()
+    assert headers["api-key"] == "test-key"
+    assert headers["Content-Type"] == "application/json"
+    print("✅ Header building works correctly")
+    
+    # Test payload preparation
+    messages = [{"role": "user", "content": "Test"}]
+    payload = provider._prepare_request_payload("gpt-4o-deployment", messages, max_tokens=1000)
+    assert payload["max_completion_tokens"] == 1000  # Azure 2024-10-21 format
+    print("✅ Payload preparation works correctly")
+    
+    print("✅ All basic tests passed! Updated test file is working correctly.")

tests/test_base_channel.py

@@ -0,0 +1,25 @@
+from types import SimpleNamespace
+
+from nanobot.bus.events import OutboundMessage
+from nanobot.bus.queue import MessageBus
+from nanobot.channels.base import BaseChannel
+
+
+class _DummyChannel(BaseChannel):
+    name = "dummy"
+
+    async def start(self) -> None:
+        return None
+
+    async def stop(self) -> None:
+        return None
+
+    async def send(self, msg: OutboundMessage) -> None:
+        return None
+
+
+def test_is_allowed_requires_exact_match() -> None:
+    channel = _DummyChannel(SimpleNamespace(allow_from=["allow@email.com"]), MessageBus())
+
+    assert channel.is_allowed("allow@email.com") is True
+    assert channel.is_allowed("attacker|allow@email.com") is False

tests/test_commands.py

@@ -1,6 +1,6 @@
 import shutil
 from pathlib import Path
-from unittest.mock import patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from typer.testing import CliRunner
@@ -14,13 +14,17 @@ from nanobot.providers.registry import find_by_model
 runner = CliRunner()
 
 
+class _StopGateway(RuntimeError):
+    pass
+
+
 @pytest.fixture
 def mock_paths():
     """Mock config/workspace paths for test isolation."""
     with patch("nanobot.config.loader.get_config_path") as mock_cp, \
          patch("nanobot.config.loader.save_config") as mock_sc, \
          patch("nanobot.config.loader.load_config") as mock_lc, \
-         patch("nanobot.utils.helpers.get_workspace_path") as mock_ws:
+         patch("nanobot.cli.commands.get_workspace_path") as mock_ws:
 
         base_dir = Path("./test_onboard_data")
         if base_dir.exists():
@@ -110,6 +114,35 @@ def test_config_matches_openai_codex_with_hyphen_prefix():
     assert config.get_provider_name() == "openai_codex"
 
 
+def test_config_matches_explicit_ollama_prefix_without_api_key():
+    config = Config()
+    config.agents.defaults.model = "ollama/llama3.2"
+
+    assert config.get_provider_name() == "ollama"
+    assert config.get_api_base() == "http://localhost:11434"
+
+
+def test_config_explicit_ollama_provider_uses_default_localhost_api_base():
+    config = Config()
+    config.agents.defaults.provider = "ollama"
+    config.agents.defaults.model = "llama3.2"
+
+    assert config.get_provider_name() == "ollama"
+    assert config.get_api_base() == "http://localhost:11434"
+
+
+def test_config_auto_detects_ollama_from_local_api_base():
+    config = Config.model_validate(
+        {
+            "agents": {"defaults": {"provider": "auto", "model": "llama3.2"}},
+            "providers": {"ollama": {"apiBase": "http://localhost:11434"}},
+        }
+    )
+
+    assert config.get_provider_name() == "ollama"
+    assert config.get_api_base() == "http://localhost:11434"
+
+
 def test_find_by_model_prefers_explicit_prefix_over_generic_codex_keyword():
     spec = find_by_model("github-copilot/gpt-5.3-codex")
 
@@ -128,3 +161,303 @@ def test_litellm_provider_canonicalizes_github_copilot_hyphen_prefix():
 def test_openai_codex_strip_prefix_supports_hyphen_and_underscore():
     assert _strip_model_prefix("openai-codex/gpt-5.1-codex") == "gpt-5.1-codex"
     assert _strip_model_prefix("openai_codex/gpt-5.1-codex") == "gpt-5.1-codex"
+
+
+@pytest.fixture
+def mock_agent_runtime(tmp_path):
+    """Mock agent command dependencies for focused CLI tests."""
+    config = Config()
+    config.agents.defaults.workspace = str(tmp_path / "default-workspace")
+    cron_dir = tmp_path / "data" / "cron"
+
+    with patch("nanobot.config.loader.load_config", return_value=config) as mock_load_config, \
+         patch("nanobot.config.paths.get_cron_dir", return_value=cron_dir), \
+         patch("nanobot.cli.commands.sync_workspace_templates") as mock_sync_templates, \
+         patch("nanobot.cli.commands._make_provider", return_value=object()), \
+         patch("nanobot.cli.commands._print_agent_response") as mock_print_response, \
+         patch("nanobot.bus.queue.MessageBus"), \
+         patch("nanobot.cron.service.CronService"), \
+         patch("nanobot.agent.loop.AgentLoop") as mock_agent_loop_cls:
+
+        agent_loop = MagicMock()
+        agent_loop.channels_config = None
+        agent_loop.process_direct = AsyncMock(return_value="mock-response")
+        agent_loop.close_mcp = AsyncMock(return_value=None)
+        mock_agent_loop_cls.return_value = agent_loop
+
+        yield {
+            "config": config,
+            "load_config": mock_load_config,
+            "sync_templates": mock_sync_templates,
+            "agent_loop_cls": mock_agent_loop_cls,
+            "agent_loop": agent_loop,
+            "print_response": mock_print_response,
+        }
+
+
+def test_agent_help_shows_workspace_and_config_options():
+    result = runner.invoke(app, ["agent", "--help"])
+
+    assert result.exit_code == 0
+    assert "--workspace" in result.stdout
+    assert "-w" in result.stdout
+    assert "--config" in result.stdout
+    assert "-c" in result.stdout
+
+
+def test_agent_uses_default_config_when_no_workspace_or_config_flags(mock_agent_runtime):
+    result = runner.invoke(app, ["agent", "-m", "hello"])
+
+    assert result.exit_code == 0
+    assert mock_agent_runtime["load_config"].call_args.args == (None,)
+    assert mock_agent_runtime["sync_templates"].call_args.args == (
+        mock_agent_runtime["config"].workspace_path,
+    )
+    assert mock_agent_runtime["agent_loop_cls"].call_args.kwargs["workspace"] == (
+        mock_agent_runtime["config"].workspace_path
+    )
+    mock_agent_runtime["agent_loop"].process_direct.assert_awaited_once()
+    mock_agent_runtime["print_response"].assert_called_once_with("mock-response", render_markdown=True)
+
+
+def test_agent_uses_explicit_config_path(mock_agent_runtime, tmp_path: Path):
+    config_path = tmp_path / "agent-config.json"
+    config_path.write_text("{}")
+
+    result = runner.invoke(app, ["agent", "-m", "hello", "-c", str(config_path)])
+
+    assert result.exit_code == 0
+    assert mock_agent_runtime["load_config"].call_args.args == (config_path.resolve(),)
+
+
+def test_agent_config_sets_active_path(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    seen: dict[str, Path] = {}
+
+    monkeypatch.setattr(
+        "nanobot.config.loader.set_config_path",
+        lambda path: seen.__setitem__("config_path", path),
+    )
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr("nanobot.config.paths.get_cron_dir", lambda: config_file.parent / "cron")
+    monkeypatch.setattr("nanobot.cli.commands.sync_workspace_templates", lambda _path: None)
+    monkeypatch.setattr("nanobot.cli.commands._make_provider", lambda _config: object())
+    monkeypatch.setattr("nanobot.bus.queue.MessageBus", lambda: object())
+    monkeypatch.setattr("nanobot.cron.service.CronService", lambda _store: object())
+
+    class _FakeAgentLoop:
+        def __init__(self, *args, **kwargs) -> None:
+            pass
+
+        async def process_direct(self, *_args, **_kwargs) -> str:
+            return "ok"
+
+        async def close_mcp(self) -> None:
+            return None
+
+    monkeypatch.setattr("nanobot.agent.loop.AgentLoop", _FakeAgentLoop)
+    monkeypatch.setattr("nanobot.cli.commands._print_agent_response", lambda *_args, **_kwargs: None)
+
+    result = runner.invoke(app, ["agent", "-m", "hello", "-c", str(config_file)])
+
+    assert result.exit_code == 0
+    assert seen["config_path"] == config_file.resolve()
+
+
+def test_agent_overrides_workspace_path(mock_agent_runtime):
+    workspace_path = Path("/tmp/agent-workspace")
+
+    result = runner.invoke(app, ["agent", "-m", "hello", "-w", str(workspace_path)])
+
+    assert result.exit_code == 0
+    assert mock_agent_runtime["config"].agents.defaults.workspace == str(workspace_path)
+    assert mock_agent_runtime["sync_templates"].call_args.args == (workspace_path,)
+    assert mock_agent_runtime["agent_loop_cls"].call_args.kwargs["workspace"] == workspace_path
+
+
+def test_agent_workspace_override_wins_over_config_workspace(mock_agent_runtime, tmp_path: Path):
+    config_path = tmp_path / "agent-config.json"
+    config_path.write_text("{}")
+    workspace_path = Path("/tmp/agent-workspace")
+
+    result = runner.invoke(
+        app,
+        ["agent", "-m", "hello", "-c", str(config_path), "-w", str(workspace_path)],
+    )
+
+    assert result.exit_code == 0
+    assert mock_agent_runtime["load_config"].call_args.args == (config_path.resolve(),)
+    assert mock_agent_runtime["config"].agents.defaults.workspace == str(workspace_path)
+    assert mock_agent_runtime["sync_templates"].call_args.args == (workspace_path,)
+    assert mock_agent_runtime["agent_loop_cls"].call_args.kwargs["workspace"] == workspace_path
+
+
+def test_agent_warns_about_deprecated_memory_window(mock_agent_runtime):
+    mock_agent_runtime["config"].agents.defaults.memory_window = 100
+
+    result = runner.invoke(app, ["agent", "-m", "hello"])
+
+    assert result.exit_code == 0
+    assert "memoryWindow" in result.stdout
+    assert "contextWindowTokens" in result.stdout
+
+
+def test_gateway_uses_workspace_from_config_by_default(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    config.agents.defaults.workspace = str(tmp_path / "config-workspace")
+    seen: dict[str, Path] = {}
+
+    monkeypatch.setattr(
+        "nanobot.config.loader.set_config_path",
+        lambda path: seen.__setitem__("config_path", path),
+    )
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr(
+        "nanobot.cli.commands.sync_workspace_templates",
+        lambda path: seen.__setitem__("workspace", path),
+    )
+    monkeypatch.setattr(
+        "nanobot.cli.commands._make_provider",
+        lambda _config: (_ for _ in ()).throw(_StopGateway("stop")),
+    )
+
+    result = runner.invoke(app, ["gateway", "--config", str(config_file)])
+
+    assert isinstance(result.exception, _StopGateway)
+    assert seen["config_path"] == config_file.resolve()
+    assert seen["workspace"] == Path(config.agents.defaults.workspace)
+
+
+def test_gateway_workspace_option_overrides_config(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    config.agents.defaults.workspace = str(tmp_path / "config-workspace")
+    override = tmp_path / "override-workspace"
+    seen: dict[str, Path] = {}
+
+    monkeypatch.setattr("nanobot.config.loader.set_config_path", lambda _path: None)
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr(
+        "nanobot.cli.commands.sync_workspace_templates",
+        lambda path: seen.__setitem__("workspace", path),
+    )
+    monkeypatch.setattr(
+        "nanobot.cli.commands._make_provider",
+        lambda _config: (_ for _ in ()).throw(_StopGateway("stop")),
+    )
+
+    result = runner.invoke(
+        app,
+        ["gateway", "--config", str(config_file), "--workspace", str(override)],
+    )
+
+    assert isinstance(result.exception, _StopGateway)
+    assert seen["workspace"] == override
+    assert config.workspace_path == override
+
+
+def test_gateway_warns_about_deprecated_memory_window(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    config.agents.defaults.memory_window = 100
+
+    monkeypatch.setattr("nanobot.config.loader.set_config_path", lambda _path: None)
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr("nanobot.cli.commands.sync_workspace_templates", lambda _path: None)
+    monkeypatch.setattr(
+        "nanobot.cli.commands._make_provider",
+        lambda _config: (_ for _ in ()).throw(_StopGateway("stop")),
+    )
+
+    result = runner.invoke(app, ["gateway", "--config", str(config_file)])
+
+    assert isinstance(result.exception, _StopGateway)
+    assert "memoryWindow" in result.stdout
+    assert "contextWindowTokens" in result.stdout
+
+def test_gateway_uses_config_directory_for_cron_store(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    config.agents.defaults.workspace = str(tmp_path / "config-workspace")
+    seen: dict[str, Path] = {}
+
+    monkeypatch.setattr("nanobot.config.loader.set_config_path", lambda _path: None)
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr("nanobot.config.paths.get_cron_dir", lambda: config_file.parent / "cron")
+    monkeypatch.setattr("nanobot.cli.commands.sync_workspace_templates", lambda _path: None)
+    monkeypatch.setattr("nanobot.cli.commands._make_provider", lambda _config: object())
+    monkeypatch.setattr("nanobot.bus.queue.MessageBus", lambda: object())
+    monkeypatch.setattr("nanobot.session.manager.SessionManager", lambda _workspace: object())
+
+    class _StopCron:
+        def __init__(self, store_path: Path) -> None:
+            seen["cron_store"] = store_path
+            raise _StopGateway("stop")
+
+    monkeypatch.setattr("nanobot.cron.service.CronService", _StopCron)
+
+    result = runner.invoke(app, ["gateway", "--config", str(config_file)])
+
+    assert isinstance(result.exception, _StopGateway)
+    assert seen["cron_store"] == config_file.parent / "cron" / "jobs.json"
+
+
+def test_gateway_uses_configured_port_when_cli_flag_is_missing(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    config.gateway.port = 18791
+
+    monkeypatch.setattr("nanobot.config.loader.set_config_path", lambda _path: None)
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr("nanobot.cli.commands.sync_workspace_templates", lambda _path: None)
+    monkeypatch.setattr(
+        "nanobot.cli.commands._make_provider",
+        lambda _config: (_ for _ in ()).throw(_StopGateway("stop")),
+    )
+
+    result = runner.invoke(app, ["gateway", "--config", str(config_file)])
+
+    assert isinstance(result.exception, _StopGateway)
+    assert "port 18791" in result.stdout
+
+
+def test_gateway_cli_port_overrides_configured_port(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance" / "config.json"
+    config_file.parent.mkdir(parents=True)
+    config_file.write_text("{}")
+
+    config = Config()
+    config.gateway.port = 18791
+
+    monkeypatch.setattr("nanobot.config.loader.set_config_path", lambda _path: None)
+    monkeypatch.setattr("nanobot.config.loader.load_config", lambda _path=None: config)
+    monkeypatch.setattr("nanobot.cli.commands.sync_workspace_templates", lambda _path: None)
+    monkeypatch.setattr(
+        "nanobot.cli.commands._make_provider",
+        lambda _config: (_ for _ in ()).throw(_StopGateway("stop")),
+    )
+
+    result = runner.invoke(app, ["gateway", "--config", str(config_file), "--port", "18792"])
+
+    assert isinstance(result.exception, _StopGateway)
+    assert "port 18792" in result.stdout

tests/test_config_migration.py

@@ -0,0 +1,88 @@
+import json
+
+from typer.testing import CliRunner
+
+from nanobot.cli.commands import app
+from nanobot.config.loader import load_config, save_config
+
+runner = CliRunner()
+
+
+def test_load_config_keeps_max_tokens_and_warns_on_legacy_memory_window(tmp_path) -> None:
+    config_path = tmp_path / "config.json"
+    config_path.write_text(
+        json.dumps(
+            {
+                "agents": {
+                    "defaults": {
+                        "maxTokens": 1234,
+                        "memoryWindow": 42,
+                    }
+                }
+            }
+        ),
+        encoding="utf-8",
+    )
+
+    config = load_config(config_path)
+
+    assert config.agents.defaults.max_tokens == 1234
+    assert config.agents.defaults.context_window_tokens == 65_536
+    assert config.agents.defaults.should_warn_deprecated_memory_window is True
+
+
+def test_save_config_writes_context_window_tokens_but_not_memory_window(tmp_path) -> None:
+    config_path = tmp_path / "config.json"
+    config_path.write_text(
+        json.dumps(
+            {
+                "agents": {
+                    "defaults": {
+                        "maxTokens": 2222,
+                        "memoryWindow": 30,
+                    }
+                }
+            }
+        ),
+        encoding="utf-8",
+    )
+
+    config = load_config(config_path)
+    save_config(config, config_path)
+    saved = json.loads(config_path.read_text(encoding="utf-8"))
+    defaults = saved["agents"]["defaults"]
+
+    assert defaults["maxTokens"] == 2222
+    assert defaults["contextWindowTokens"] == 65_536
+    assert "memoryWindow" not in defaults
+
+
+def test_onboard_refresh_rewrites_legacy_config_template(tmp_path, monkeypatch) -> None:
+    config_path = tmp_path / "config.json"
+    workspace = tmp_path / "workspace"
+    config_path.write_text(
+        json.dumps(
+            {
+                "agents": {
+                    "defaults": {
+                        "maxTokens": 3333,
+                        "memoryWindow": 50,
+                    }
+                }
+            }
+        ),
+        encoding="utf-8",
+    )
+
+    monkeypatch.setattr("nanobot.config.loader.get_config_path", lambda: config_path)
+    monkeypatch.setattr("nanobot.cli.commands.get_workspace_path", lambda: workspace)
+
+    result = runner.invoke(app, ["onboard"], input="n\n")
+
+    assert result.exit_code == 0
+    assert "contextWindowTokens" in result.stdout
+    saved = json.loads(config_path.read_text(encoding="utf-8"))
+    defaults = saved["agents"]["defaults"]
+    assert defaults["maxTokens"] == 3333
+    assert defaults["contextWindowTokens"] == 65_536
+    assert "memoryWindow" not in defaults

tests/test_config_paths.py

@@ -0,0 +1,42 @@
+from pathlib import Path
+
+from nanobot.config.paths import (
+    get_bridge_install_dir,
+    get_cli_history_path,
+    get_cron_dir,
+    get_data_dir,
+    get_legacy_sessions_dir,
+    get_logs_dir,
+    get_media_dir,
+    get_runtime_subdir,
+    get_workspace_path,
+)
+
+
+def test_runtime_dirs_follow_config_path(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance-a" / "config.json"
+    monkeypatch.setattr("nanobot.config.paths.get_config_path", lambda: config_file)
+
+    assert get_data_dir() == config_file.parent
+    assert get_runtime_subdir("cron") == config_file.parent / "cron"
+    assert get_cron_dir() == config_file.parent / "cron"
+    assert get_logs_dir() == config_file.parent / "logs"
+
+
+def test_media_dir_supports_channel_namespace(monkeypatch, tmp_path: Path) -> None:
+    config_file = tmp_path / "instance-b" / "config.json"
+    monkeypatch.setattr("nanobot.config.paths.get_config_path", lambda: config_file)
+
+    assert get_media_dir() == config_file.parent / "media"
+    assert get_media_dir("telegram") == config_file.parent / "media" / "telegram"
+
+
+def test_shared_and_legacy_paths_remain_global() -> None:
+    assert get_cli_history_path() == Path.home() / ".nanobot" / "history" / "cli_history"
+    assert get_bridge_install_dir() == Path.home() / ".nanobot" / "bridge"
+    assert get_legacy_sessions_dir() == Path.home() / ".nanobot" / "sessions"
+
+
+def test_workspace_path_is_explicitly_resolved() -> None:
+    assert get_workspace_path() == Path.home() / ".nanobot" / "workspace"
+    assert get_workspace_path("~/custom-workspace") == Path.home() / "custom-workspace"

tests/test_consolidate_offset.py

@@ -480,226 +480,35 @@ class TestEmptyAndBoundarySessions:
         assert_messages_content(old_messages, 10, 34)
 
 
-class TestConsolidationDeduplicationGuard:
+class TestNewCommandArchival:
-    """Test that consolidation tasks are deduplicated and serialized."""
+    """Test /new archival behavior with the simplified consolidation flow."""
 
-    @pytest.mark.asyncio
+    @staticmethod
-    async def test_consolidation_guard_prevents_duplicate_tasks(self, tmp_path: Path) -> None:
+    def _make_loop(tmp_path: Path):
-        """Concurrent messages above memory_window spawn only one consolidation task."""
         from nanobot.agent.loop import AgentLoop
-        from nanobot.bus.events import InboundMessage
         from nanobot.bus.queue import MessageBus
         from nanobot.providers.base import LLMResponse
 
         bus = MessageBus()
         provider = MagicMock()
         provider.get_default_model.return_value = "test-model"
+        provider.estimate_prompt_tokens.return_value = (10_000, "test")
         loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
+            bus=bus,
+            provider=provider,
+            workspace=tmp_path,
+            model="test-model",
+            context_window_tokens=1,
         )
-
+        loop.provider.chat_with_retry = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
         loop.tools.get_definitions = MagicMock(return_value=[])
-
+        return loop
-        session = loop.sessions.get_or_create("cli:test")
-        for i in range(15):
-            session.add_message("user", f"msg{i}")
-            session.add_message("assistant", f"resp{i}")
-        loop.sessions.save(session)
-
-        consolidation_calls = 0
-
-        async def _fake_consolidate(_session, archive_all: bool = False) -> None:
-            nonlocal consolidation_calls
-            consolidation_calls += 1
-            await asyncio.sleep(0.05)
-
-        loop._consolidate_memory = _fake_consolidate  # type: ignore[method-assign]
-
-        msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="hello")
-        await loop._process_message(msg)
-        await loop._process_message(msg)
-        await asyncio.sleep(0.1)
-
-        assert consolidation_calls == 1, (
-            f"Expected exactly 1 consolidation, got {consolidation_calls}"
-        )
-
-    @pytest.mark.asyncio
-    async def test_new_command_guard_prevents_concurrent_consolidation(
-        self, tmp_path: Path
-    ) -> None:
-        """/new command does not run consolidation concurrently with in-flight consolidation."""
-        from nanobot.agent.loop import AgentLoop
-        from nanobot.bus.events import InboundMessage
-        from nanobot.bus.queue import MessageBus
-        from nanobot.providers.base import LLMResponse
-
-        bus = MessageBus()
-        provider = MagicMock()
-        provider.get_default_model.return_value = "test-model"
-        loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
-        )
-
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.tools.get_definitions = MagicMock(return_value=[])
-
-        session = loop.sessions.get_or_create("cli:test")
-        for i in range(15):
-            session.add_message("user", f"msg{i}")
-            session.add_message("assistant", f"resp{i}")
-        loop.sessions.save(session)
-
-        consolidation_calls = 0
-        active = 0
-        max_active = 0
-
-        async def _fake_consolidate(_session, archive_all: bool = False) -> None:
-            nonlocal consolidation_calls, active, max_active
-            consolidation_calls += 1
-            active += 1
-            max_active = max(max_active, active)
-            await asyncio.sleep(0.05)
-            active -= 1
-
-        loop._consolidate_memory = _fake_consolidate  # type: ignore[method-assign]
-
-        msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="hello")
-        await loop._process_message(msg)
-
-        new_msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="/new")
-        await loop._process_message(new_msg)
-        await asyncio.sleep(0.1)
-
-        assert consolidation_calls == 2, (
-            f"Expected normal + /new consolidations, got {consolidation_calls}"
-        )
-        assert max_active == 1, (
-            f"Expected serialized consolidation, observed concurrency={max_active}"
-        )
-
-    @pytest.mark.asyncio
-    async def test_consolidation_tasks_are_referenced(self, tmp_path: Path) -> None:
-        """create_task results are tracked in _consolidation_tasks while in flight."""
-        from nanobot.agent.loop import AgentLoop
-        from nanobot.bus.events import InboundMessage
-        from nanobot.bus.queue import MessageBus
-        from nanobot.providers.base import LLMResponse
-
-        bus = MessageBus()
-        provider = MagicMock()
-        provider.get_default_model.return_value = "test-model"
-        loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
-        )
-
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.tools.get_definitions = MagicMock(return_value=[])
-
-        session = loop.sessions.get_or_create("cli:test")
-        for i in range(15):
-            session.add_message("user", f"msg{i}")
-            session.add_message("assistant", f"resp{i}")
-        loop.sessions.save(session)
-
-        started = asyncio.Event()
-
-        async def _slow_consolidate(_session, archive_all: bool = False) -> None:
-            started.set()
-            await asyncio.sleep(0.1)
-
-        loop._consolidate_memory = _slow_consolidate  # type: ignore[method-assign]
-
-        msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="hello")
-        await loop._process_message(msg)
-
-        await started.wait()
-        assert len(loop._consolidation_tasks) == 1, "Task must be referenced while in-flight"
-
-        await asyncio.sleep(0.15)
-        assert len(loop._consolidation_tasks) == 0, (
-            "Task reference must be removed after completion"
-        )
-
-    @pytest.mark.asyncio
-    async def test_new_waits_for_inflight_consolidation_and_preserves_messages(
-        self, tmp_path: Path
-    ) -> None:
-        """/new waits for in-flight consolidation and archives before clear."""
-        from nanobot.agent.loop import AgentLoop
-        from nanobot.bus.events import InboundMessage
-        from nanobot.bus.queue import MessageBus
-        from nanobot.providers.base import LLMResponse
-
-        bus = MessageBus()
-        provider = MagicMock()
-        provider.get_default_model.return_value = "test-model"
-        loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
-        )
-
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.tools.get_definitions = MagicMock(return_value=[])
-
-        session = loop.sessions.get_or_create("cli:test")
-        for i in range(15):
-            session.add_message("user", f"msg{i}")
-            session.add_message("assistant", f"resp{i}")
-        loop.sessions.save(session)
-
-        started = asyncio.Event()
-        release = asyncio.Event()
-        archived_count = 0
-
-        async def _fake_consolidate(sess, archive_all: bool = False) -> bool:
-            nonlocal archived_count
-            if archive_all:
-                archived_count = len(sess.messages)
-                return True
-            started.set()
-            await release.wait()
-            return True
-
-        loop._consolidate_memory = _fake_consolidate  # type: ignore[method-assign]
-
-        msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="hello")
-        await loop._process_message(msg)
-        await started.wait()
-
-        new_msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="/new")
-        pending_new = asyncio.create_task(loop._process_message(new_msg))
-
-        await asyncio.sleep(0.02)
-        assert not pending_new.done(), "/new should wait while consolidation is in-flight"
-
-        release.set()
-        response = await pending_new
-        assert response is not None
-        assert "new session started" in response.content.lower()
-        assert archived_count > 0, "Expected /new archival to process a non-empty snapshot"
-
-        session_after = loop.sessions.get_or_create("cli:test")
-        assert session_after.messages == [], "Session should be cleared after successful archival"
 
     @pytest.mark.asyncio
     async def test_new_does_not_clear_session_when_archive_fails(self, tmp_path: Path) -> None:
-        """/new must keep session data if archive step reports failure."""
-        from nanobot.agent.loop import AgentLoop
         from nanobot.bus.events import InboundMessage
-        from nanobot.bus.queue import MessageBus
-        from nanobot.providers.base import LLMResponse
-
-        bus = MessageBus()
-        provider = MagicMock()
-        provider.get_default_model.return_value = "test-model"
-        loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
-        )
-
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.tools.get_definitions = MagicMock(return_value=[])
 
+        loop = self._make_loop(tmp_path)
         session = loop.sessions.get_or_create("cli:test")
         for i in range(5):
             session.add_message("user", f"msg{i}")
@@ -707,111 +516,61 @@ class TestConsolidationDeduplicationGuard:
         loop.sessions.save(session)
         before_count = len(session.messages)
 
-        async def _failing_consolidate(sess, archive_all: bool = False) -> bool:
+        async def _failing_consolidate(_messages) -> bool:
-            if archive_all:
+            return False
-                return False
-            return True
 
-        loop._consolidate_memory = _failing_consolidate  # type: ignore[method-assign]
+        loop.memory_consolidator.consolidate_messages = _failing_consolidate  # type: ignore[method-assign]
 
         new_msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="/new")
         response = await loop._process_message(new_msg)
 
         assert response is not None
         assert "failed" in response.content.lower()
-        session_after = loop.sessions.get_or_create("cli:test")
+        assert len(loop.sessions.get_or_create("cli:test").messages) == before_count
-        assert len(session_after.messages) == before_count, (
-            "Session must remain intact when /new archival fails"
-        )
 
     @pytest.mark.asyncio
-    async def test_new_archives_only_unconsolidated_messages_after_inflight_task(
+    async def test_new_archives_only_unconsolidated_messages(self, tmp_path: Path) -> None:
-        self, tmp_path: Path
-    ) -> None:
-        """/new should archive only messages not yet consolidated by prior task."""
-        from nanobot.agent.loop import AgentLoop
         from nanobot.bus.events import InboundMessage
-        from nanobot.bus.queue import MessageBus
-        from nanobot.providers.base import LLMResponse
-
-        bus = MessageBus()
-        provider = MagicMock()
-        provider.get_default_model.return_value = "test-model"
-        loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
-        )
-
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.tools.get_definitions = MagicMock(return_value=[])
 
+        loop = self._make_loop(tmp_path)
         session = loop.sessions.get_or_create("cli:test")
         for i in range(15):
             session.add_message("user", f"msg{i}")
             session.add_message("assistant", f"resp{i}")
+        session.last_consolidated = len(session.messages) - 3
         loop.sessions.save(session)
 
-        started = asyncio.Event()
-        release = asyncio.Event()
         archived_count = -1
 
-        async def _fake_consolidate(sess, archive_all: bool = False) -> bool:
+        async def _fake_consolidate(messages) -> bool:
             nonlocal archived_count
-            if archive_all:
+            archived_count = len(messages)
-                archived_count = len(sess.messages)
-                return True
-
-            started.set()
-            await release.wait()
-            sess.last_consolidated = len(sess.messages) - 3
             return True
 
-        loop._consolidate_memory = _fake_consolidate  # type: ignore[method-assign]
+        loop.memory_consolidator.consolidate_messages = _fake_consolidate  # type: ignore[method-assign]
-
-        msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="hello")
-        await loop._process_message(msg)
-        await started.wait()
 
         new_msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="/new")
-        pending_new = asyncio.create_task(loop._process_message(new_msg))
+        response = await loop._process_message(new_msg)
-        await asyncio.sleep(0.02)
-        assert not pending_new.done()
-
-        release.set()
-        response = await pending_new
 
         assert response is not None
         assert "new session started" in response.content.lower()
-        assert archived_count == 3, (
+        assert archived_count == 3
-            f"Expected only unconsolidated tail to archive, got {archived_count}"
-        )
 
     @pytest.mark.asyncio
     async def test_new_clears_session_and_responds(self, tmp_path: Path) -> None:
-        """/new clears session and returns confirmation."""
-        from nanobot.agent.loop import AgentLoop
         from nanobot.bus.events import InboundMessage
-        from nanobot.bus.queue import MessageBus
-        from nanobot.providers.base import LLMResponse
-
-        bus = MessageBus()
-        provider = MagicMock()
-        provider.get_default_model.return_value = "test-model"
-        loop = AgentLoop(
-            bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10
-        )
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
-        loop.tools.get_definitions = MagicMock(return_value=[])
 
+        loop = self._make_loop(tmp_path)
         session = loop.sessions.get_or_create("cli:test")
         for i in range(3):
             session.add_message("user", f"msg{i}")
             session.add_message("assistant", f"resp{i}")
         loop.sessions.save(session)
 
-        async def _ok_consolidate(sess, archive_all: bool = False) -> bool:
+        async def _ok_consolidate(_messages) -> bool:
             return True
 
-        loop._consolidate_memory = _ok_consolidate  # type: ignore[method-assign]
+        loop.memory_consolidator.consolidate_messages = _ok_consolidate  # type: ignore[method-assign]
 
         new_msg = InboundMessage(channel="cli", sender_id="user", chat_id="test", content="/new")
         response = await loop._process_message(new_msg)

tests/test_context_prompt_cache.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 from datetime import datetime as real_datetime
+from importlib.resources import files as pkg_files
 from pathlib import Path
 import datetime as datetime_module
 
@@ -23,6 +24,13 @@ def _make_workspace(tmp_path: Path) -> Path:
     return workspace
 
 
+def test_bootstrap_files_are_backed_by_templates() -> None:
+    template_dir = pkg_files("nanobot") / "templates"
+
+    for filename in ContextBuilder.BOOTSTRAP_FILES:
+        assert (template_dir / filename).is_file(), f"missing bootstrap template: {filename}"
+
+
 def test_system_prompt_stays_stable_when_clock_changes(tmp_path, monkeypatch) -> None:
     """System prompt should not change just because wall clock minute changes."""
     monkeypatch.setattr(datetime_module, "datetime", _FakeDatetime)
@@ -40,7 +48,7 @@ def test_system_prompt_stays_stable_when_clock_changes(tmp_path, monkeypatch) ->
 
 
 def test_runtime_context_is_separate_untrusted_user_message(tmp_path) -> None:
-    """Runtime metadata should be a separate user message before the actual user message."""
+    """Runtime metadata should be merged with the user message."""
     workspace = _make_workspace(tmp_path)
     builder = ContextBuilder(workspace)
 
@@ -54,13 +62,12 @@ def test_runtime_context_is_separate_untrusted_user_message(tmp_path) -> None:
     assert messages[0]["role"] == "system"
     assert "## Current Session" not in messages[0]["content"]
 
-    assert messages[-2]["role"] == "user"
+    # Runtime context is now merged with user message into a single message
-    runtime_content = messages[-2]["content"]
-    assert isinstance(runtime_content, str)
-    assert ContextBuilder._RUNTIME_CONTEXT_TAG in runtime_content
-    assert "Current Time:" in runtime_content
-    assert "Channel: cli" in runtime_content
-    assert "Chat ID: direct" in runtime_content
-
     assert messages[-1]["role"] == "user"
-    assert messages[-1]["content"] == "Return exactly: OK"
+    user_content = messages[-1]["content"]
+    assert isinstance(user_content, str)
+    assert ContextBuilder._RUNTIME_CONTEXT_TAG in user_content
+    assert "Current Time:" in user_content
+    assert "Channel: cli" in user_content
+    assert "Chat ID: direct" in user_content
+    assert "Return exactly: OK" in user_content

tests/test_cron_commands.py

@@ -1,29 +0,0 @@
-from typer.testing import CliRunner
-
-from nanobot.cli.commands import app
-
-runner = CliRunner()
-
-
-def test_cron_add_rejects_invalid_timezone(monkeypatch, tmp_path) -> None:
-    monkeypatch.setattr("nanobot.config.loader.get_data_dir", lambda: tmp_path)
-
-    result = runner.invoke(
-        app,
-        [
-            "cron",
-            "add",
-            "--name",
-            "demo",
-            "--message",
-            "hello",
-            "--cron",
-            "0 9 * * *",
-            "--tz",
-            "America/Vancovuer",
-        ],
-    )
-
-    assert result.exit_code == 1
-    assert "Error: unknown timezone 'America/Vancovuer'" in result.stdout
-    assert not (tmp_path / "cron" / "jobs.json").exists()

tests/test_cron_service.py

@@ -48,6 +48,8 @@ async def test_running_service_honors_external_disable(tmp_path) -> None:
     )
     await service.start()
     try:
+        # Wait slightly to ensure file mtime is definitively different
+        await asyncio.sleep(0.05)
         external = CronService(store_path)
         updated = external.enable_job(job.id, enabled=False)
         assert updated is not None

tests/test_dingtalk_channel.py

@@ -0,0 +1,111 @@
+import asyncio
+from types import SimpleNamespace
+
+import pytest
+
+from nanobot.bus.queue import MessageBus
+import nanobot.channels.dingtalk as dingtalk_module
+from nanobot.channels.dingtalk import DingTalkChannel, NanobotDingTalkHandler
+from nanobot.config.schema import DingTalkConfig
+
+
+class _FakeResponse:
+    def __init__(self, status_code: int = 200, json_body: dict | None = None) -> None:
+        self.status_code = status_code
+        self._json_body = json_body or {}
+        self.text = "{}"
+
+    def json(self) -> dict:
+        return self._json_body
+
+
+class _FakeHttp:
+    def __init__(self) -> None:
+        self.calls: list[dict] = []
+
+    async def post(self, url: str, json=None, headers=None):
+        self.calls.append({"url": url, "json": json, "headers": headers})
+        return _FakeResponse()
+
+
+@pytest.mark.asyncio
+async def test_group_message_keeps_sender_id_and_routes_chat_id() -> None:
+    config = DingTalkConfig(client_id="app", client_secret="secret", allow_from=["user1"])
+    bus = MessageBus()
+    channel = DingTalkChannel(config, bus)
+
+    await channel._on_message(
+        "hello",
+        sender_id="user1",
+        sender_name="Alice",
+        conversation_type="2",
+        conversation_id="conv123",
+    )
+
+    msg = await bus.consume_inbound()
+    assert msg.sender_id == "user1"
+    assert msg.chat_id == "group:conv123"
+    assert msg.metadata["conversation_type"] == "2"
+
+
+@pytest.mark.asyncio
+async def test_group_send_uses_group_messages_api() -> None:
+    config = DingTalkConfig(client_id="app", client_secret="secret", allow_from=["*"])
+    channel = DingTalkChannel(config, MessageBus())
+    channel._http = _FakeHttp()
+
+    ok = await channel._send_batch_message(
+        "token",
+        "group:conv123",
+        "sampleMarkdown",
+        {"text": "hello", "title": "Nanobot Reply"},
+    )
+
+    assert ok is True
+    call = channel._http.calls[0]
+    assert call["url"] == "https://api.dingtalk.com/v1.0/robot/groupMessages/send"
+    assert call["json"]["openConversationId"] == "conv123"
+    assert call["json"]["msgKey"] == "sampleMarkdown"
+
+
+@pytest.mark.asyncio
+async def test_handler_uses_voice_recognition_text_when_text_is_empty(monkeypatch) -> None:
+    bus = MessageBus()
+    channel = DingTalkChannel(
+        DingTalkConfig(client_id="app", client_secret="secret", allow_from=["user1"]),
+        bus,
+    )
+    handler = NanobotDingTalkHandler(channel)
+
+    class _FakeChatbotMessage:
+        text = None
+        extensions = {"content": {"recognition": "voice transcript"}}
+        sender_staff_id = "user1"
+        sender_id = "fallback-user"
+        sender_nick = "Alice"
+        message_type = "audio"
+
+        @staticmethod
+        def from_dict(_data):
+            return _FakeChatbotMessage()
+
+    monkeypatch.setattr(dingtalk_module, "ChatbotMessage", _FakeChatbotMessage)
+    monkeypatch.setattr(dingtalk_module, "AckMessage", SimpleNamespace(STATUS_OK="OK"))
+
+    status, body = await handler.process(
+        SimpleNamespace(
+            data={
+                "conversationType": "2",
+                "conversationId": "conv123",
+                "text": {"content": ""},
+            }
+        )
+    )
+
+    await asyncio.gather(*list(channel._background_tasks))
+    msg = await bus.consume_inbound()
+
+    assert (status, body) == ("OK", "OK")
+    assert msg.content == "voice transcript"
+    assert msg.sender_id == "user1"
+    assert msg.chat_id == "group:conv123"

tests/test_feishu_post_content.py

@@ -1,4 +1,4 @@
-from nanobot.channels.feishu import _extract_post_content
+from nanobot.channels.feishu import FeishuChannel, _extract_post_content
 
 
 def test_extract_post_content_supports_post_wrapper_shape() -> None:
@@ -38,3 +38,28 @@ def test_extract_post_content_keeps_direct_shape_behavior() -> None:
 
     assert text == "Daily report"
     assert image_keys == ["img_a", "img_b"]
+
+
+def test_register_optional_event_keeps_builder_when_method_missing() -> None:
+    class Builder:
+        pass
+
+    builder = Builder()
+    same = FeishuChannel._register_optional_event(builder, "missing", object())
+    assert same is builder
+
+
+def test_register_optional_event_calls_supported_method() -> None:
+    called = []
+
+    class Builder:
+        def register_event(self, handler):
+            called.append(handler)
+            return self
+
+    builder = Builder()
+    handler = object()
+    same = FeishuChannel._register_optional_event(builder, "register_event", handler)
+
+    assert same is builder
+    assert called == [handler]

tests/test_feishu_table_split.py

@@ -0,0 +1,104 @@
+"""Tests for FeishuChannel._split_elements_by_table_limit.
+
+Feishu cards reject messages that contain more than one table element
+(API error 11310: card table number over limit).  The helper splits a flat
+list of card elements into groups so that each group contains at most one
+table, allowing nanobot to send multiple cards instead of failing.
+"""
+
+from nanobot.channels.feishu import FeishuChannel
+
+
+def _md(text: str) -> dict:
+    return {"tag": "markdown", "content": text}
+
+
+def _table() -> dict:
+    return {
+        "tag": "table",
+        "columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
+        "rows": [{"c0": "v"}],
+        "page_size": 2,
+    }
+
+
+split = FeishuChannel._split_elements_by_table_limit
+
+
+def test_empty_list_returns_single_empty_group() -> None:
+    assert split([]) == [[]]
+
+
+def test_no_tables_returns_single_group() -> None:
+    els = [_md("hello"), _md("world")]
+    result = split(els)
+    assert result == [els]
+
+
+def test_single_table_stays_in_one_group() -> None:
+    els = [_md("intro"), _table(), _md("outro")]
+    result = split(els)
+    assert len(result) == 1
+    assert result[0] == els
+
+
+def test_two_tables_split_into_two_groups() -> None:
+    # Use different row values so the two tables are not equal
+    t1 = {
+        "tag": "table",
+        "columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
+        "rows": [{"c0": "table-one"}],
+        "page_size": 2,
+    }
+    t2 = {
+        "tag": "table",
+        "columns": [{"tag": "column", "name": "c0", "display_name": "B", "width": "auto"}],
+        "rows": [{"c0": "table-two"}],
+        "page_size": 2,
+    }
+    els = [_md("before"), t1, _md("between"), t2, _md("after")]
+    result = split(els)
+    assert len(result) == 2
+    # First group: text before table-1 + table-1
+    assert t1 in result[0]
+    assert t2 not in result[0]
+    # Second group: text between tables + table-2 + text after
+    assert t2 in result[1]
+    assert t1 not in result[1]
+
+
+def test_three_tables_split_into_three_groups() -> None:
+    tables = [
+        {"tag": "table", "columns": [], "rows": [{"c0": f"t{i}"}], "page_size": 1}
+        for i in range(3)
+    ]
+    els = tables[:]
+    result = split(els)
+    assert len(result) == 3
+    for i, group in enumerate(result):
+        assert tables[i] in group
+
+
+def test_leading_markdown_stays_with_first_table() -> None:
+    intro = _md("intro")
+    t = _table()
+    result = split([intro, t])
+    assert len(result) == 1
+    assert result[0] == [intro, t]
+
+
+def test_trailing_markdown_after_second_table() -> None:
+    t1, t2 = _table(), _table()
+    tail = _md("end")
+    result = split([t1, t2, tail])
+    assert len(result) == 2
+    assert result[1] == [t2, tail]
+
+
+def test_non_table_elements_before_first_table_kept_in_first_group() -> None:
+    head = _md("head")
+    t1, t2 = _table(), _table()
+    result = split([head, t1, t2])
+    # head + t1 in group 0; t2 in group 1
+    assert result[0] == [head, t1]
+    assert result[1] == [t2]

tests/test_filesystem_tools.py

@@ -0,0 +1,251 @@
+"""Tests for enhanced filesystem tools: ReadFileTool, EditFileTool, ListDirTool."""
+
+import pytest
+
+from nanobot.agent.tools.filesystem import (
+    EditFileTool,
+    ListDirTool,
+    ReadFileTool,
+    _find_match,
+)
+
+
+# ---------------------------------------------------------------------------
+# ReadFileTool
+# ---------------------------------------------------------------------------
+
+class TestReadFileTool:
+
+    @pytest.fixture()
+    def tool(self, tmp_path):
+        return ReadFileTool(workspace=tmp_path)
+
+    @pytest.fixture()
+    def sample_file(self, tmp_path):
+        f = tmp_path / "sample.txt"
+        f.write_text("\n".join(f"line {i}" for i in range(1, 21)), encoding="utf-8")
+        return f
+
+    @pytest.mark.asyncio
+    async def test_basic_read_has_line_numbers(self, tool, sample_file):
+        result = await tool.execute(path=str(sample_file))
+        assert "1| line 1" in result
+        assert "20| line 20" in result
+
+    @pytest.mark.asyncio
+    async def test_offset_and_limit(self, tool, sample_file):
+        result = await tool.execute(path=str(sample_file), offset=5, limit=3)
+        assert "5| line 5" in result
+        assert "7| line 7" in result
+        assert "8| line 8" not in result
+        assert "Use offset=8 to continue" in result
+
+    @pytest.mark.asyncio
+    async def test_offset_beyond_end(self, tool, sample_file):
+        result = await tool.execute(path=str(sample_file), offset=999)
+        assert "Error" in result
+        assert "beyond end" in result
+
+    @pytest.mark.asyncio
+    async def test_end_of_file_marker(self, tool, sample_file):
+        result = await tool.execute(path=str(sample_file), offset=1, limit=9999)
+        assert "End of file" in result
+
+    @pytest.mark.asyncio
+    async def test_empty_file(self, tool, tmp_path):
+        f = tmp_path / "empty.txt"
+        f.write_text("", encoding="utf-8")
+        result = await tool.execute(path=str(f))
+        assert "Empty file" in result
+
+    @pytest.mark.asyncio
+    async def test_file_not_found(self, tool, tmp_path):
+        result = await tool.execute(path=str(tmp_path / "nope.txt"))
+        assert "Error" in result
+        assert "not found" in result
+
+    @pytest.mark.asyncio
+    async def test_char_budget_trims(self, tool, tmp_path):
+        """When the selected slice exceeds _MAX_CHARS the output is trimmed."""
+        f = tmp_path / "big.txt"
+        # Each line is ~110 chars, 2000 lines ≈ 220 KB > 128 KB limit
+        f.write_text("\n".join("x" * 110 for _ in range(2000)), encoding="utf-8")
+        result = await tool.execute(path=str(f))
+        assert len(result) <= ReadFileTool._MAX_CHARS + 500  # small margin for footer
+        assert "Use offset=" in result
+
+
+# ---------------------------------------------------------------------------
+# _find_match  (unit tests for the helper)
+# ---------------------------------------------------------------------------
+
+class TestFindMatch:
+
+    def test_exact_match(self):
+        match, count = _find_match("hello world", "world")
+        assert match == "world"
+        assert count == 1
+
+    def test_exact_no_match(self):
+        match, count = _find_match("hello world", "xyz")
+        assert match is None
+        assert count == 0
+
+    def test_crlf_normalisation(self):
+        # Caller normalises CRLF before calling _find_match, so test with
+        # pre-normalised content to verify exact match still works.
+        content = "line1\nline2\nline3"
+        old_text = "line1\nline2\nline3"
+        match, count = _find_match(content, old_text)
+        assert match is not None
+        assert count == 1
+
+    def test_line_trim_fallback(self):
+        content = "    def foo():\n        pass\n"
+        old_text = "def foo():\n    pass"
+        match, count = _find_match(content, old_text)
+        assert match is not None
+        assert count == 1
+        # The returned match should be the *original* indented text
+        assert "    def foo():" in match
+
+    def test_line_trim_multiple_candidates(self):
+        content = "  a\n  b\n  a\n  b\n"
+        old_text = "a\nb"
+        match, count = _find_match(content, old_text)
+        assert count == 2
+
+    def test_empty_old_text(self):
+        match, count = _find_match("hello", "")
+        # Empty string is always "in" any string via exact match
+        assert match == ""
+
+
+# ---------------------------------------------------------------------------
+# EditFileTool
+# ---------------------------------------------------------------------------
+
+class TestEditFileTool:
+
+    @pytest.fixture()
+    def tool(self, tmp_path):
+        return EditFileTool(workspace=tmp_path)
+
+    @pytest.mark.asyncio
+    async def test_exact_match(self, tool, tmp_path):
+        f = tmp_path / "a.py"
+        f.write_text("hello world", encoding="utf-8")
+        result = await tool.execute(path=str(f), old_text="world", new_text="earth")
+        assert "Successfully" in result
+        assert f.read_text() == "hello earth"
+
+    @pytest.mark.asyncio
+    async def test_crlf_normalisation(self, tool, tmp_path):
+        f = tmp_path / "crlf.py"
+        f.write_bytes(b"line1\r\nline2\r\nline3")
+        result = await tool.execute(
+            path=str(f), old_text="line1\nline2", new_text="LINE1\nLINE2",
+        )
+        assert "Successfully" in result
+        raw = f.read_bytes()
+        assert b"LINE1" in raw
+        # CRLF line endings should be preserved throughout the file
+        assert b"\r\n" in raw
+
+    @pytest.mark.asyncio
+    async def test_trim_fallback(self, tool, tmp_path):
+        f = tmp_path / "indent.py"
+        f.write_text("    def foo():\n        pass\n", encoding="utf-8")
+        result = await tool.execute(
+            path=str(f), old_text="def foo():\n    pass", new_text="def bar():\n    return 1",
+        )
+        assert "Successfully" in result
+        assert "bar" in f.read_text()
+
+    @pytest.mark.asyncio
+    async def test_ambiguous_match(self, tool, tmp_path):
+        f = tmp_path / "dup.py"
+        f.write_text("aaa\nbbb\naaa\nbbb\n", encoding="utf-8")
+        result = await tool.execute(path=str(f), old_text="aaa\nbbb", new_text="xxx")
+        assert "appears" in result.lower() or "Warning" in result
+
+    @pytest.mark.asyncio
+    async def test_replace_all(self, tool, tmp_path):
+        f = tmp_path / "multi.py"
+        f.write_text("foo bar foo bar foo", encoding="utf-8")
+        result = await tool.execute(
+            path=str(f), old_text="foo", new_text="baz", replace_all=True,
+        )
+        assert "Successfully" in result
+        assert f.read_text() == "baz bar baz bar baz"
+
+    @pytest.mark.asyncio
+    async def test_not_found(self, tool, tmp_path):
+        f = tmp_path / "nf.py"
+        f.write_text("hello", encoding="utf-8")
+        result = await tool.execute(path=str(f), old_text="xyz", new_text="abc")
+        assert "Error" in result
+        assert "not found" in result
+
+
+# ---------------------------------------------------------------------------
+# ListDirTool
+# ---------------------------------------------------------------------------
+
+class TestListDirTool:
+
+    @pytest.fixture()
+    def tool(self, tmp_path):
+        return ListDirTool(workspace=tmp_path)
+
+    @pytest.fixture()
+    def populated_dir(self, tmp_path):
+        (tmp_path / "src").mkdir()
+        (tmp_path / "src" / "main.py").write_text("pass")
+        (tmp_path / "src" / "utils.py").write_text("pass")
+        (tmp_path / "README.md").write_text("hi")
+        (tmp_path / ".git").mkdir()
+        (tmp_path / ".git" / "config").write_text("x")
+        (tmp_path / "node_modules").mkdir()
+        (tmp_path / "node_modules" / "pkg").mkdir()
+        return tmp_path
+
+    @pytest.mark.asyncio
+    async def test_basic_list(self, tool, populated_dir):
+        result = await tool.execute(path=str(populated_dir))
+        assert "README.md" in result
+        assert "src" in result
+        # .git and node_modules should be ignored
+        assert ".git" not in result
+        assert "node_modules" not in result
+
+    @pytest.mark.asyncio
+    async def test_recursive(self, tool, populated_dir):
+        result = await tool.execute(path=str(populated_dir), recursive=True)
+        assert "src/main.py" in result
+        assert "src/utils.py" in result
+        assert "README.md" in result
+        # Ignored dirs should not appear
+        assert ".git" not in result
+        assert "node_modules" not in result
+
+    @pytest.mark.asyncio
+    async def test_max_entries_truncation(self, tool, tmp_path):
+        for i in range(10):
+            (tmp_path / f"file_{i}.txt").write_text("x")
+        result = await tool.execute(path=str(tmp_path), max_entries=3)
+        assert "truncated" in result
+        assert "3 of 10" in result
+
+    @pytest.mark.asyncio
+    async def test_empty_dir(self, tool, tmp_path):
+        d = tmp_path / "empty"
+        d.mkdir()
+        result = await tool.execute(path=str(d))
+        assert "empty" in result.lower()
+
+    @pytest.mark.asyncio
+    async def test_not_found(self, tool, tmp_path):
+        result = await tool.execute(path=str(tmp_path / "nope"))
+        assert "Error" in result
+        assert "not found" in result

tests/test_gemini_thought_signature.py

@@ -0,0 +1,53 @@
+from types import SimpleNamespace
+
+from nanobot.providers.base import ToolCallRequest
+from nanobot.providers.litellm_provider import LiteLLMProvider
+
+
+def test_litellm_parse_response_preserves_tool_call_provider_fields() -> None:
+    provider = LiteLLMProvider(default_model="gemini/gemini-3-flash")
+
+    response = SimpleNamespace(
+        choices=[
+            SimpleNamespace(
+                finish_reason="tool_calls",
+                message=SimpleNamespace(
+                    content=None,
+                    tool_calls=[
+                        SimpleNamespace(
+                            id="call_123",
+                            function=SimpleNamespace(
+                                name="read_file",
+                                arguments='{"path":"todo.md"}',
+                                provider_specific_fields={"inner": "value"},
+                            ),
+                            provider_specific_fields={"thought_signature": "signed-token"},
+                        )
+                    ],
+                ),
+            )
+        ],
+        usage=None,
+    )
+
+    parsed = provider._parse_response(response)
+
+    assert len(parsed.tool_calls) == 1
+    assert parsed.tool_calls[0].provider_specific_fields == {"thought_signature": "signed-token"}
+    assert parsed.tool_calls[0].function_provider_specific_fields == {"inner": "value"}
+
+
+def test_tool_call_request_serializes_provider_fields() -> None:
+    tool_call = ToolCallRequest(
+        id="abc123xyz",
+        name="read_file",
+        arguments={"path": "todo.md"},
+        provider_specific_fields={"thought_signature": "signed-token"},
+        function_provider_specific_fields={"inner": "value"},
+    )
+
+    message = tool_call.to_openai_tool_call()
+
+    assert message["provider_specific_fields"] == {"thought_signature": "signed-token"}
+    assert message["function"]["provider_specific_fields"] == {"inner": "value"}
+    assert message["function"]["arguments"] == '{"path": "todo.md"}'

tests/test_heartbeat_service.py

@@ -3,18 +3,24 @@ import asyncio
 import pytest
 
 from nanobot.heartbeat.service import HeartbeatService
-from nanobot.providers.base import LLMResponse, ToolCallRequest
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
 
 
-class DummyProvider:
+class DummyProvider(LLMProvider):
     def __init__(self, responses: list[LLMResponse]):
+        super().__init__()
         self._responses = list(responses)
+        self.calls = 0
 
     async def chat(self, *args, **kwargs) -> LLMResponse:
+        self.calls += 1
         if self._responses:
             return self._responses.pop(0)
         return LLMResponse(content="", tool_calls=[])
 
+    def get_default_model(self) -> str:
+        return "test-model"
+
 
 @pytest.mark.asyncio
 async def test_start_is_idempotent(tmp_path) -> None:
@@ -115,3 +121,40 @@ async def test_trigger_now_returns_none_when_decision_is_skip(tmp_path) -> None:
     )
 
     assert await service.trigger_now() is None
+
+
+@pytest.mark.asyncio
+async def test_decide_retries_transient_error_then_succeeds(tmp_path, monkeypatch) -> None:
+    provider = DummyProvider([
+        LLMResponse(content="429 rate limit", finish_reason="error"),
+        LLMResponse(
+            content="",
+            tool_calls=[
+                ToolCallRequest(
+                    id="hb_1",
+                    name="heartbeat",
+                    arguments={"action": "run", "tasks": "check open tasks"},
+                )
+            ],
+        ),
+    ])
+
+    delays: list[int] = []
+
+    async def _fake_sleep(delay: int) -> None:
+        delays.append(delay)
+
+    monkeypatch.setattr(asyncio, "sleep", _fake_sleep)
+
+    service = HeartbeatService(
+        workspace=tmp_path,
+        provider=provider,
+        model="openai/gpt-4o-mini",
+    )
+
+    action, tasks = await service._decide("heartbeat content")
+
+    assert action == "run"
+    assert tasks == "check open tasks"
+    assert provider.calls == 2
+    assert delays == [1]

tests/test_loop_consolidation_tokens.py

@@ -0,0 +1,190 @@
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from nanobot.agent.loop import AgentLoop
+import nanobot.agent.memory as memory_module
+from nanobot.bus.queue import MessageBus
+from nanobot.providers.base import LLMResponse
+
+
+def _make_loop(tmp_path, *, estimated_tokens: int, context_window_tokens: int) -> AgentLoop:
+    provider = MagicMock()
+    provider.get_default_model.return_value = "test-model"
+    provider.estimate_prompt_tokens.return_value = (estimated_tokens, "test-counter")
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(content="ok", tool_calls=[]))
+
+    loop = AgentLoop(
+        bus=MessageBus(),
+        provider=provider,
+        workspace=tmp_path,
+        model="test-model",
+        context_window_tokens=context_window_tokens,
+    )
+    loop.tools.get_definitions = MagicMock(return_value=[])
+    return loop
+
+
+@pytest.mark.asyncio
+async def test_prompt_below_threshold_does_not_consolidate(tmp_path) -> None:
+    loop = _make_loop(tmp_path, estimated_tokens=100, context_window_tokens=200)
+    loop.memory_consolidator.consolidate_messages = AsyncMock(return_value=True)  # type: ignore[method-assign]
+
+    await loop.process_direct("hello", session_key="cli:test")
+
+    loop.memory_consolidator.consolidate_messages.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_prompt_above_threshold_triggers_consolidation(tmp_path, monkeypatch) -> None:
+    loop = _make_loop(tmp_path, estimated_tokens=1000, context_window_tokens=200)
+    loop.memory_consolidator.consolidate_messages = AsyncMock(return_value=True)  # type: ignore[method-assign]
+    session = loop.sessions.get_or_create("cli:test")
+    session.messages = [
+        {"role": "user", "content": "u1", "timestamp": "2026-01-01T00:00:00"},
+        {"role": "assistant", "content": "a1", "timestamp": "2026-01-01T00:00:01"},
+        {"role": "user", "content": "u2", "timestamp": "2026-01-01T00:00:02"},
+    ]
+    loop.sessions.save(session)
+    monkeypatch.setattr(memory_module, "estimate_message_tokens", lambda _message: 500)
+
+    await loop.process_direct("hello", session_key="cli:test")
+
+    assert loop.memory_consolidator.consolidate_messages.await_count >= 1
+
+
+@pytest.mark.asyncio
+async def test_prompt_above_threshold_archives_until_next_user_boundary(tmp_path, monkeypatch) -> None:
+    loop = _make_loop(tmp_path, estimated_tokens=1000, context_window_tokens=200)
+    loop.memory_consolidator.consolidate_messages = AsyncMock(return_value=True)  # type: ignore[method-assign]
+
+    session = loop.sessions.get_or_create("cli:test")
+    session.messages = [
+        {"role": "user", "content": "u1", "timestamp": "2026-01-01T00:00:00"},
+        {"role": "assistant", "content": "a1", "timestamp": "2026-01-01T00:00:01"},
+        {"role": "user", "content": "u2", "timestamp": "2026-01-01T00:00:02"},
+        {"role": "assistant", "content": "a2", "timestamp": "2026-01-01T00:00:03"},
+        {"role": "user", "content": "u3", "timestamp": "2026-01-01T00:00:04"},
+    ]
+    loop.sessions.save(session)
+
+    token_map = {"u1": 120, "a1": 120, "u2": 120, "a2": 120, "u3": 120}
+    monkeypatch.setattr(memory_module, "estimate_message_tokens", lambda message: token_map[message["content"]])
+
+    await loop.memory_consolidator.maybe_consolidate_by_tokens(session)
+
+    archived_chunk = loop.memory_consolidator.consolidate_messages.await_args.args[0]
+    assert [message["content"] for message in archived_chunk] == ["u1", "a1", "u2", "a2"]
+    assert session.last_consolidated == 4
+
+
+@pytest.mark.asyncio
+async def test_consolidation_loops_until_target_met(tmp_path, monkeypatch) -> None:
+    """Verify maybe_consolidate_by_tokens keeps looping until under threshold."""
+    loop = _make_loop(tmp_path, estimated_tokens=0, context_window_tokens=200)
+    loop.memory_consolidator.consolidate_messages = AsyncMock(return_value=True)  # type: ignore[method-assign]
+
+    session = loop.sessions.get_or_create("cli:test")
+    session.messages = [
+        {"role": "user", "content": "u1", "timestamp": "2026-01-01T00:00:00"},
+        {"role": "assistant", "content": "a1", "timestamp": "2026-01-01T00:00:01"},
+        {"role": "user", "content": "u2", "timestamp": "2026-01-01T00:00:02"},
+        {"role": "assistant", "content": "a2", "timestamp": "2026-01-01T00:00:03"},
+        {"role": "user", "content": "u3", "timestamp": "2026-01-01T00:00:04"},
+        {"role": "assistant", "content": "a3", "timestamp": "2026-01-01T00:00:05"},
+        {"role": "user", "content": "u4", "timestamp": "2026-01-01T00:00:06"},
+    ]
+    loop.sessions.save(session)
+
+    call_count = [0]
+    def mock_estimate(_session):
+        call_count[0] += 1
+        if call_count[0] == 1:
+            return (500, "test")
+        if call_count[0] == 2:
+            return (300, "test")
+        return (80, "test")
+
+    loop.memory_consolidator.estimate_session_prompt_tokens = mock_estimate  # type: ignore[method-assign]
+    monkeypatch.setattr(memory_module, "estimate_message_tokens", lambda _m: 100)
+
+    await loop.memory_consolidator.maybe_consolidate_by_tokens(session)
+
+    assert loop.memory_consolidator.consolidate_messages.await_count == 2
+    assert session.last_consolidated == 6
+
+
+@pytest.mark.asyncio
+async def test_consolidation_continues_below_trigger_until_half_target(tmp_path, monkeypatch) -> None:
+    """Once triggered, consolidation should continue until it drops below half threshold."""
+    loop = _make_loop(tmp_path, estimated_tokens=0, context_window_tokens=200)
+    loop.memory_consolidator.consolidate_messages = AsyncMock(return_value=True)  # type: ignore[method-assign]
+
+    session = loop.sessions.get_or_create("cli:test")
+    session.messages = [
+        {"role": "user", "content": "u1", "timestamp": "2026-01-01T00:00:00"},
+        {"role": "assistant", "content": "a1", "timestamp": "2026-01-01T00:00:01"},
+        {"role": "user", "content": "u2", "timestamp": "2026-01-01T00:00:02"},
+        {"role": "assistant", "content": "a2", "timestamp": "2026-01-01T00:00:03"},
+        {"role": "user", "content": "u3", "timestamp": "2026-01-01T00:00:04"},
+        {"role": "assistant", "content": "a3", "timestamp": "2026-01-01T00:00:05"},
+        {"role": "user", "content": "u4", "timestamp": "2026-01-01T00:00:06"},
+    ]
+    loop.sessions.save(session)
+
+    call_count = [0]
+
+    def mock_estimate(_session):
+        call_count[0] += 1
+        if call_count[0] == 1:
+            return (500, "test")
+        if call_count[0] == 2:
+            return (150, "test")
+        return (80, "test")
+
+    loop.memory_consolidator.estimate_session_prompt_tokens = mock_estimate  # type: ignore[method-assign]
+    monkeypatch.setattr(memory_module, "estimate_message_tokens", lambda _m: 100)
+
+    await loop.memory_consolidator.maybe_consolidate_by_tokens(session)
+
+    assert loop.memory_consolidator.consolidate_messages.await_count == 2
+    assert session.last_consolidated == 6
+
+
+@pytest.mark.asyncio
+async def test_preflight_consolidation_before_llm_call(tmp_path, monkeypatch) -> None:
+    """Verify preflight consolidation runs before the LLM call in process_direct."""
+    order: list[str] = []
+
+    loop = _make_loop(tmp_path, estimated_tokens=0, context_window_tokens=200)
+
+    async def track_consolidate(messages):
+        order.append("consolidate")
+        return True
+    loop.memory_consolidator.consolidate_messages = track_consolidate  # type: ignore[method-assign]
+
+    async def track_llm(*args, **kwargs):
+        order.append("llm")
+        return LLMResponse(content="ok", tool_calls=[])
+    loop.provider.chat_with_retry = track_llm
+
+    session = loop.sessions.get_or_create("cli:test")
+    session.messages = [
+        {"role": "user", "content": "u1", "timestamp": "2026-01-01T00:00:00"},
+        {"role": "assistant", "content": "a1", "timestamp": "2026-01-01T00:00:01"},
+        {"role": "user", "content": "u2", "timestamp": "2026-01-01T00:00:02"},
+    ]
+    loop.sessions.save(session)
+    monkeypatch.setattr(memory_module, "estimate_message_tokens", lambda _m: 500)
+
+    call_count = [0]
+    def mock_estimate(_session):
+        call_count[0] += 1
+        return (1000 if call_count[0] <= 1 else 80, "test")
+    loop.memory_consolidator.estimate_session_prompt_tokens = mock_estimate  # type: ignore[method-assign]
+
+    await loop.process_direct("hello", session_key="cli:test")
+
+    assert "consolidate" in order
+    assert "llm" in order
+    assert order.index("consolidate") < order.index("llm")

tests/test_loop_save_turn.py

@@ -0,0 +1,41 @@
+from nanobot.agent.context import ContextBuilder
+from nanobot.agent.loop import AgentLoop
+from nanobot.session.manager import Session
+
+
+def _mk_loop() -> AgentLoop:
+    loop = AgentLoop.__new__(AgentLoop)
+    loop._TOOL_RESULT_MAX_CHARS = 500
+    return loop
+
+
+def test_save_turn_skips_multimodal_user_when_only_runtime_context() -> None:
+    loop = _mk_loop()
+    session = Session(key="test:runtime-only")
+    runtime = ContextBuilder._RUNTIME_CONTEXT_TAG + "\nCurrent Time: now (UTC)"
+
+    loop._save_turn(
+        session,
+        [{"role": "user", "content": [{"type": "text", "text": runtime}]}],
+        skip=0,
+    )
+    assert session.messages == []
+
+
+def test_save_turn_keeps_image_placeholder_after_runtime_strip() -> None:
+    loop = _mk_loop()
+    session = Session(key="test:image")
+    runtime = ContextBuilder._RUNTIME_CONTEXT_TAG + "\nCurrent Time: now (UTC)"
+
+    loop._save_turn(
+        session,
+        [{
+            "role": "user",
+            "content": [
+                {"type": "text", "text": runtime},
+                {"type": "image_url", "image_url": {"url": "data:image/png;base64,abc"}},
+            ],
+        }],
+        skip=0,
+    )
+    assert session.messages[0]["content"] == [{"type": "text", "text": "[image]"}]

tests/test_matrix_channel.py

@@ -159,6 +159,7 @@ class _FakeAsyncClient:
 
 
 def _make_config(**kwargs) -> MatrixConfig:
+    kwargs.setdefault("allow_from", ["*"])
     return MatrixConfig(
         enabled=True,
         homeserver="https://matrix.org",
@@ -274,7 +275,7 @@ async def test_stop_stops_sync_forever_before_close(monkeypatch) -> None:
 
 
 @pytest.mark.asyncio
-async def test_room_invite_joins_when_allow_list_is_empty() -> None:
+async def test_room_invite_ignores_when_allow_list_is_empty() -> None:
     channel = MatrixChannel(_make_config(allow_from=[]), MessageBus())
     client = _FakeAsyncClient("", "", "", None)
     channel.client = client
@@ -284,9 +285,22 @@ async def test_room_invite_joins_when_allow_list_is_empty() -> None:
 
     await channel._on_room_invite(room, event)
 
-    assert client.join_calls == ["!room:matrix.org"]
+    assert client.join_calls == []
 
 
+@pytest.mark.asyncio
+async def test_room_invite_joins_when_sender_allowed() -> None:
+    channel = MatrixChannel(_make_config(allow_from=["@alice:matrix.org"]), MessageBus())
+    client = _FakeAsyncClient("", "", "", None)
+    channel.client = client
+
+    room = SimpleNamespace(room_id="!room:matrix.org")
+    event = SimpleNamespace(sender="@alice:matrix.org")
+
+    await channel._on_room_invite(room, event)
+
+    assert client.join_calls == ["!room:matrix.org"]
+
 @pytest.mark.asyncio
 async def test_room_invite_respects_allow_list_when_configured() -> None:
     channel = MatrixChannel(_make_config(allow_from=["@bob:matrix.org"]), MessageBus())
@@ -1163,6 +1177,8 @@ async def test_send_progress_keeps_typing_keepalive_running() -> None:
     assert "!room:matrix.org" in channel._typing_tasks
     assert client.typing_calls[-1] == ("!room:matrix.org", True, TYPING_NOTICE_TIMEOUT_MS)
 
+    await channel.stop()
+
 
 @pytest.mark.asyncio
 async def test_send_clears_typing_when_send_fails() -> None:

tests/test_mcp_tool.py

@@ -0,0 +1,99 @@
+from __future__ import annotations
+
+import asyncio
+import sys
+from types import ModuleType, SimpleNamespace
+
+import pytest
+
+from nanobot.agent.tools.mcp import MCPToolWrapper
+
+
+class _FakeTextContent:
+    def __init__(self, text: str) -> None:
+        self.text = text
+
+
+@pytest.fixture(autouse=True)
+def _fake_mcp_module(monkeypatch: pytest.MonkeyPatch) -> None:
+    mod = ModuleType("mcp")
+    mod.types = SimpleNamespace(TextContent=_FakeTextContent)
+    monkeypatch.setitem(sys.modules, "mcp", mod)
+
+
+def _make_wrapper(session: object, *, timeout: float = 0.1) -> MCPToolWrapper:
+    tool_def = SimpleNamespace(
+        name="demo",
+        description="demo tool",
+        inputSchema={"type": "object", "properties": {}},
+    )
+    return MCPToolWrapper(session, "test", tool_def, tool_timeout=timeout)
+
+
+@pytest.mark.asyncio
+async def test_execute_returns_text_blocks() -> None:
+    async def call_tool(_name: str, arguments: dict) -> object:
+        assert arguments == {"value": 1}
+        return SimpleNamespace(content=[_FakeTextContent("hello"), 42])
+
+    wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
+
+    result = await wrapper.execute(value=1)
+
+    assert result == "hello\n42"
+
+
+@pytest.mark.asyncio
+async def test_execute_returns_timeout_message() -> None:
+    async def call_tool(_name: str, arguments: dict) -> object:
+        await asyncio.sleep(1)
+        return SimpleNamespace(content=[])
+
+    wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool), timeout=0.01)
+
+    result = await wrapper.execute()
+
+    assert result == "(MCP tool call timed out after 0.01s)"
+
+
+@pytest.mark.asyncio
+async def test_execute_handles_server_cancelled_error() -> None:
+    async def call_tool(_name: str, arguments: dict) -> object:
+        raise asyncio.CancelledError()
+
+    wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
+
+    result = await wrapper.execute()
+
+    assert result == "(MCP tool call was cancelled)"
+
+
+@pytest.mark.asyncio
+async def test_execute_re_raises_external_cancellation() -> None:
+    started = asyncio.Event()
+
+    async def call_tool(_name: str, arguments: dict) -> object:
+        started.set()
+        await asyncio.sleep(60)
+        return SimpleNamespace(content=[])
+
+    wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool), timeout=10)
+    task = asyncio.create_task(wrapper.execute())
+    await started.wait()
+
+    task.cancel()
+
+    with pytest.raises(asyncio.CancelledError):
+        await task
+
+
+@pytest.mark.asyncio
+async def test_execute_handles_generic_exception() -> None:
+    async def call_tool(_name: str, arguments: dict) -> object:
+        raise RuntimeError("boom")
+
+    wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
+
+    result = await wrapper.execute()
+
+    assert result == "(MCP tool call failed: RuntimeError)"

tests/test_memory_consolidation_types.py

@@ -7,23 +7,20 @@ tool call response, it should serialize them to JSON instead of raising TypeErro
 
 import json
 from pathlib import Path
-from unittest.mock import AsyncMock, MagicMock
+from unittest.mock import AsyncMock
 
 import pytest
 
 from nanobot.agent.memory import MemoryStore
-from nanobot.providers.base import LLMResponse, ToolCallRequest
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
 
 
-def _make_session(message_count: int = 30, memory_window: int = 50):
+def _make_messages(message_count: int = 30):
-    """Create a mock session with messages."""
+    """Create a list of mock messages."""
-    session = MagicMock()
+    return [
-    session.messages = [
         {"role": "user", "content": f"msg{i}", "timestamp": "2026-01-01 00:00"}
         for i in range(message_count)
     ]
-    session.last_consolidated = 0
-    return session
 
 
 def _make_tool_response(history_entry, memory_update):
@@ -43,6 +40,22 @@ def _make_tool_response(history_entry, memory_update):
     )
 
 
+class ScriptedProvider(LLMProvider):
+    def __init__(self, responses: list[LLMResponse]):
+        super().__init__()
+        self._responses = list(responses)
+        self.calls = 0
+
+    async def chat(self, *args, **kwargs) -> LLMResponse:
+        self.calls += 1
+        if self._responses:
+            return self._responses.pop(0)
+        return LLMResponse(content="", tool_calls=[])
+
+    def get_default_model(self) -> str:
+        return "test-model"
+
+
 class TestMemoryConsolidationTypeHandling:
     """Test that consolidation handles various argument types correctly."""
 
@@ -57,9 +70,10 @@ class TestMemoryConsolidationTypeHandling:
                 memory_update="# Memory\nUser likes testing.",
             )
         )
-        session = _make_session(message_count=60)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
 
-        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+        result = await store.consolidate(messages, provider, "test-model")
 
         assert result is True
         assert store.history_file.exists()
@@ -77,9 +91,10 @@ class TestMemoryConsolidationTypeHandling:
                 memory_update={"facts": ["User likes testing"], "topics": ["testing"]},
             )
         )
-        session = _make_session(message_count=60)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
 
-        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+        result = await store.consolidate(messages, provider, "test-model")
 
         assert result is True
         assert store.history_file.exists()
@@ -112,9 +127,10 @@ class TestMemoryConsolidationTypeHandling:
             ],
         )
         provider.chat = AsyncMock(return_value=response)
-        session = _make_session(message_count=60)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
 
-        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+        result = await store.consolidate(messages, provider, "test-model")
 
         assert result is True
         assert "User discussed testing." in store.history_file.read_text()
@@ -127,21 +143,148 @@ class TestMemoryConsolidationTypeHandling:
         provider.chat = AsyncMock(
             return_value=LLMResponse(content="I summarized the conversation.", tool_calls=[])
         )
-        session = _make_session(message_count=60)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
 
-        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+        result = await store.consolidate(messages, provider, "test-model")
 
         assert result is False
         assert not store.history_file.exists()
 
     @pytest.mark.asyncio
-    async def test_skips_when_few_messages(self, tmp_path: Path) -> None:
+    async def test_skips_when_message_chunk_is_empty(self, tmp_path: Path) -> None:
-        """Consolidation should be a no-op when messages < keep_count."""
+        """Consolidation should be a no-op when the selected chunk is empty."""
         store = MemoryStore(tmp_path)
         provider = AsyncMock()
-        session = _make_session(message_count=10)
+        provider.chat_with_retry = provider.chat
+        messages: list[dict] = []
 
-        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+        result = await store.consolidate(messages, provider, "test-model")
 
         assert result is True
         provider.chat.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_list_arguments_extracts_first_dict(self, tmp_path: Path) -> None:
+        """Some providers return arguments as a list - extract first element if it's a dict."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        # Simulate arguments being a list containing a dict
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=[{
+                        "history_entry": "[2026-01-01] User discussed testing.",
+                        "memory_update": "# Memory\nUser likes testing.",
+                    }],
+                )
+            ],
+        )
+        provider.chat = AsyncMock(return_value=response)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is True
+        assert "User discussed testing." in store.history_file.read_text()
+        assert "User likes testing." in store.memory_file.read_text()
+
+    @pytest.mark.asyncio
+    async def test_list_arguments_empty_list_returns_false(self, tmp_path: Path) -> None:
+        """Empty list arguments should return False."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=[],
+                )
+            ],
+        )
+        provider.chat = AsyncMock(return_value=response)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is False
+
+    @pytest.mark.asyncio
+    async def test_list_arguments_non_dict_content_returns_false(self, tmp_path: Path) -> None:
+        """List with non-dict content should return False."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=["string", "content"],
+                )
+            ],
+        )
+        provider.chat = AsyncMock(return_value=response)
+        provider.chat_with_retry = provider.chat
+        messages = _make_messages(message_count=60)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is False
+
+    @pytest.mark.asyncio
+    async def test_retries_transient_error_then_succeeds(self, tmp_path: Path, monkeypatch) -> None:
+        store = MemoryStore(tmp_path)
+        provider = ScriptedProvider([
+            LLMResponse(content="503 server error", finish_reason="error"),
+            _make_tool_response(
+                history_entry="[2026-01-01] User discussed testing.",
+                memory_update="# Memory\nUser likes testing.",
+            ),
+        ])
+        messages = _make_messages(message_count=60)
+        delays: list[int] = []
+
+        async def _fake_sleep(delay: int) -> None:
+            delays.append(delay)
+
+        monkeypatch.setattr("nanobot.providers.base.asyncio.sleep", _fake_sleep)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is True
+        assert provider.calls == 2
+        assert delays == [1]
+
+    @pytest.mark.asyncio
+    async def test_consolidation_delegates_to_provider_defaults(self, tmp_path: Path) -> None:
+        """Consolidation no longer passes generation params — the provider owns them."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+        provider.chat_with_retry = AsyncMock(
+            return_value=_make_tool_response(
+                history_entry="[2026-01-01] User discussed testing.",
+                memory_update="# Memory\nUser likes testing.",
+            )
+        )
+        messages = _make_messages(message_count=60)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is True
+        provider.chat_with_retry.assert_awaited_once()
+        _, kwargs = provider.chat_with_retry.await_args
+        assert kwargs["model"] == "test-model"
+        assert "temperature" not in kwargs
+        assert "max_tokens" not in kwargs
+        assert "reasoning_effort" not in kwargs

tests/test_message_tool_suppress.py

@@ -16,7 +16,7 @@ def _make_loop(tmp_path: Path) -> AgentLoop:
     bus = MessageBus()
     provider = MagicMock()
     provider.get_default_model.return_value = "test-model"
-    return AgentLoop(bus=bus, provider=provider, workspace=tmp_path, model="test-model", memory_window=10)
+    return AgentLoop(bus=bus, provider=provider, workspace=tmp_path, model="test-model")
 
 
 class TestMessageToolSuppressLogic:
@@ -33,7 +33,7 @@ class TestMessageToolSuppressLogic:
             LLMResponse(content="", tool_calls=[tool_call]),
             LLMResponse(content="Done", tool_calls=[]),
         ])
-        loop.provider.chat = AsyncMock(side_effect=lambda *a, **kw: next(calls))
+        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
         loop.tools.get_definitions = MagicMock(return_value=[])
 
         sent: list[OutboundMessage] = []
@@ -58,7 +58,7 @@ class TestMessageToolSuppressLogic:
             LLMResponse(content="", tool_calls=[tool_call]),
             LLMResponse(content="I've sent the email.", tool_calls=[]),
         ])
-        loop.provider.chat = AsyncMock(side_effect=lambda *a, **kw: next(calls))
+        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
         loop.tools.get_definitions = MagicMock(return_value=[])
 
         sent: list[OutboundMessage] = []
@@ -77,7 +77,7 @@ class TestMessageToolSuppressLogic:
     @pytest.mark.asyncio
     async def test_not_suppress_when_no_message_tool_used(self, tmp_path: Path) -> None:
         loop = _make_loop(tmp_path)
-        loop.provider.chat = AsyncMock(return_value=LLMResponse(content="Hello!", tool_calls=[]))
+        loop.provider.chat_with_retry = AsyncMock(return_value=LLMResponse(content="Hello!", tool_calls=[]))
         loop.tools.get_definitions = MagicMock(return_value=[])
 
         msg = InboundMessage(channel="feishu", sender_id="user1", chat_id="chat123", content="Hi")
@@ -86,6 +86,35 @@ class TestMessageToolSuppressLogic:
         assert result is not None
         assert "Hello" in result.content
 
+    async def test_progress_hides_internal_reasoning(self, tmp_path: Path) -> None:
+        loop = _make_loop(tmp_path)
+        tool_call = ToolCallRequest(id="call1", name="read_file", arguments={"path": "foo.txt"})
+        calls = iter([
+            LLMResponse(
+                content="Visible<think>hidden</think>",
+                tool_calls=[tool_call],
+                reasoning_content="secret reasoning",
+                thinking_blocks=[{"signature": "sig", "thought": "secret thought"}],
+            ),
+            LLMResponse(content="Done", tool_calls=[]),
+        ])
+        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
+        loop.tools.get_definitions = MagicMock(return_value=[])
+        loop.tools.execute = AsyncMock(return_value="ok")
+
+        progress: list[tuple[str, bool]] = []
+
+        async def on_progress(content: str, *, tool_hint: bool = False) -> None:
+            progress.append((content, tool_hint))
+
+        final_content, _, _ = await loop._run_agent_loop([], on_progress=on_progress)
+
+        assert final_content == "Done"
+        assert progress == [
+            ("Visible", False),
+            ('read_file("foo.txt")', True),
+        ]
+
 
 class TestMessageToolTurnTracking:
 

tests/test_provider_retry.py

@@ -0,0 +1,125 @@
+import asyncio
+
+import pytest
+
+from nanobot.providers.base import GenerationSettings, LLMProvider, LLMResponse
+
+
+class ScriptedProvider(LLMProvider):
+    def __init__(self, responses):
+        super().__init__()
+        self._responses = list(responses)
+        self.calls = 0
+        self.last_kwargs: dict = {}
+
+    async def chat(self, *args, **kwargs) -> LLMResponse:
+        self.calls += 1
+        self.last_kwargs = kwargs
+        response = self._responses.pop(0)
+        if isinstance(response, BaseException):
+            raise response
+        return response
+
+    def get_default_model(self) -> str:
+        return "test-model"
+
+
+@pytest.mark.asyncio
+async def test_chat_with_retry_retries_transient_error_then_succeeds(monkeypatch) -> None:
+    provider = ScriptedProvider([
+        LLMResponse(content="429 rate limit", finish_reason="error"),
+        LLMResponse(content="ok"),
+    ])
+    delays: list[int] = []
+
+    async def _fake_sleep(delay: int) -> None:
+        delays.append(delay)
+
+    monkeypatch.setattr("nanobot.providers.base.asyncio.sleep", _fake_sleep)
+
+    response = await provider.chat_with_retry(messages=[{"role": "user", "content": "hello"}])
+
+    assert response.finish_reason == "stop"
+    assert response.content == "ok"
+    assert provider.calls == 2
+    assert delays == [1]
+
+
+@pytest.mark.asyncio
+async def test_chat_with_retry_does_not_retry_non_transient_error(monkeypatch) -> None:
+    provider = ScriptedProvider([
+        LLMResponse(content="401 unauthorized", finish_reason="error"),
+    ])
+    delays: list[int] = []
+
+    async def _fake_sleep(delay: int) -> None:
+        delays.append(delay)
+
+    monkeypatch.setattr("nanobot.providers.base.asyncio.sleep", _fake_sleep)
+
+    response = await provider.chat_with_retry(messages=[{"role": "user", "content": "hello"}])
+
+    assert response.content == "401 unauthorized"
+    assert provider.calls == 1
+    assert delays == []
+
+
+@pytest.mark.asyncio
+async def test_chat_with_retry_returns_final_error_after_retries(monkeypatch) -> None:
+    provider = ScriptedProvider([
+        LLMResponse(content="429 rate limit a", finish_reason="error"),
+        LLMResponse(content="429 rate limit b", finish_reason="error"),
+        LLMResponse(content="429 rate limit c", finish_reason="error"),
+        LLMResponse(content="503 final server error", finish_reason="error"),
+    ])
+    delays: list[int] = []
+
+    async def _fake_sleep(delay: int) -> None:
+        delays.append(delay)
+
+    monkeypatch.setattr("nanobot.providers.base.asyncio.sleep", _fake_sleep)
+
+    response = await provider.chat_with_retry(messages=[{"role": "user", "content": "hello"}])
+
+    assert response.content == "503 final server error"
+    assert provider.calls == 4
+    assert delays == [1, 2, 4]
+
+
+@pytest.mark.asyncio
+async def test_chat_with_retry_preserves_cancelled_error() -> None:
+    provider = ScriptedProvider([asyncio.CancelledError()])
+
+    with pytest.raises(asyncio.CancelledError):
+        await provider.chat_with_retry(messages=[{"role": "user", "content": "hello"}])
+
+
+@pytest.mark.asyncio
+async def test_chat_with_retry_uses_provider_generation_defaults() -> None:
+    """When callers omit generation params, provider.generation defaults are used."""
+    provider = ScriptedProvider([LLMResponse(content="ok")])
+    provider.generation = GenerationSettings(temperature=0.2, max_tokens=321, reasoning_effort="high")
+
+    await provider.chat_with_retry(messages=[{"role": "user", "content": "hello"}])
+
+    assert provider.last_kwargs["temperature"] == 0.2
+    assert provider.last_kwargs["max_tokens"] == 321
+    assert provider.last_kwargs["reasoning_effort"] == "high"
+
+
+@pytest.mark.asyncio
+async def test_chat_with_retry_explicit_override_beats_defaults() -> None:
+    """Explicit kwargs should override provider.generation defaults."""
+    provider = ScriptedProvider([LLMResponse(content="ok")])
+    provider.generation = GenerationSettings(temperature=0.2, max_tokens=321, reasoning_effort="high")
+
+    await provider.chat_with_retry(
+        messages=[{"role": "user", "content": "hello"}],
+        temperature=0.9,
+        max_tokens=9999,
+        reasoning_effort="low",
+    )
+
+    assert provider.last_kwargs["temperature"] == 0.9
+    assert provider.last_kwargs["max_tokens"] == 9999
+    assert provider.last_kwargs["reasoning_effort"] == "low"

tests/test_qq_channel.py

@@ -0,0 +1,66 @@
+from types import SimpleNamespace
+
+import pytest
+
+from nanobot.bus.events import OutboundMessage
+from nanobot.bus.queue import MessageBus
+from nanobot.channels.qq import QQChannel
+from nanobot.config.schema import QQConfig
+
+
+class _FakeApi:
+    def __init__(self) -> None:
+        self.c2c_calls: list[dict] = []
+        self.group_calls: list[dict] = []
+
+    async def post_c2c_message(self, **kwargs) -> None:
+        self.c2c_calls.append(kwargs)
+
+    async def post_group_message(self, **kwargs) -> None:
+        self.group_calls.append(kwargs)
+
+
+class _FakeClient:
+    def __init__(self) -> None:
+        self.api = _FakeApi()
+
+
+@pytest.mark.asyncio
+async def test_on_group_message_routes_to_group_chat_id() -> None:
+    channel = QQChannel(QQConfig(app_id="app", secret="secret", allow_from=["user1"]), MessageBus())
+
+    data = SimpleNamespace(
+        id="msg1",
+        content="hello",
+        group_openid="group123",
+        author=SimpleNamespace(member_openid="user1"),
+    )
+
+    await channel._on_message(data, is_group=True)
+
+    msg = await channel.bus.consume_inbound()
+    assert msg.sender_id == "user1"
+    assert msg.chat_id == "group123"
+
+
+@pytest.mark.asyncio
+async def test_send_group_message_uses_group_api_with_msg_seq() -> None:
+    channel = QQChannel(QQConfig(app_id="app", secret="secret", allow_from=["*"]), MessageBus())
+    channel._client = _FakeClient()
+    channel._chat_type_cache["group123"] = "group"
+
+    await channel.send(
+        OutboundMessage(
+            channel="qq",
+            chat_id="group123",
+            content="hello",
+            metadata={"message_id": "msg1"},
+        )
+    )
+
+    assert len(channel._client.api.group_calls) == 1
+    call = channel._client.api.group_calls[0]
+    assert call["group_openid"] == "group123"
+    assert call["msg_id"] == "msg1"
+    assert call["msg_seq"] == 2
+    assert not channel._client.api.c2c_calls

tests/test_skill_creator_scripts.py

@@ -0,0 +1,127 @@
+import importlib
+import shutil
+import sys
+import zipfile
+from pathlib import Path
+
+
+SCRIPT_DIR = Path("nanobot/skills/skill-creator/scripts").resolve()
+if str(SCRIPT_DIR) not in sys.path:
+    sys.path.insert(0, str(SCRIPT_DIR))
+
+init_skill = importlib.import_module("init_skill")
+package_skill = importlib.import_module("package_skill")
+quick_validate = importlib.import_module("quick_validate")
+
+
+def test_init_skill_creates_expected_files(tmp_path: Path) -> None:
+    skill_dir = init_skill.init_skill(
+        "demo-skill",
+        tmp_path,
+        ["scripts", "references", "assets"],
+        include_examples=True,
+    )
+
+    assert skill_dir == tmp_path / "demo-skill"
+    assert (skill_dir / "SKILL.md").exists()
+    assert (skill_dir / "scripts" / "example.py").exists()
+    assert (skill_dir / "references" / "api_reference.md").exists()
+    assert (skill_dir / "assets" / "example_asset.txt").exists()
+
+
+def test_validate_skill_accepts_existing_skill_creator() -> None:
+    valid, message = quick_validate.validate_skill(
+        Path("nanobot/skills/skill-creator").resolve()
+    )
+
+    assert valid, message
+
+
+def test_validate_skill_rejects_placeholder_description(tmp_path: Path) -> None:
+    skill_dir = tmp_path / "placeholder-skill"
+    skill_dir.mkdir()
+    (skill_dir / "SKILL.md").write_text(
+        "---\n"
+        "name: placeholder-skill\n"
+        'description: "[TODO: fill me in]"\n'
+        "---\n"
+        "# Placeholder\n",
+        encoding="utf-8",
+    )
+
+    valid, message = quick_validate.validate_skill(skill_dir)
+
+    assert not valid
+    assert "TODO placeholder" in message
+
+
+def test_validate_skill_rejects_root_files_outside_allowed_dirs(tmp_path: Path) -> None:
+    skill_dir = tmp_path / "bad-root-skill"
+    skill_dir.mkdir()
+    (skill_dir / "SKILL.md").write_text(
+        "---\n"
+        "name: bad-root-skill\n"
+        "description: Valid description\n"
+        "---\n"
+        "# Skill\n",
+        encoding="utf-8",
+    )
+    (skill_dir / "README.md").write_text("extra\n", encoding="utf-8")
+
+    valid, message = quick_validate.validate_skill(skill_dir)
+
+    assert not valid
+    assert "Unexpected file or directory in skill root" in message
+
+
+def test_package_skill_creates_archive(tmp_path: Path) -> None:
+    skill_dir = tmp_path / "package-me"
+    skill_dir.mkdir()
+    (skill_dir / "SKILL.md").write_text(
+        "---\n"
+        "name: package-me\n"
+        "description: Package this skill.\n"
+        "---\n"
+        "# Skill\n",
+        encoding="utf-8",
+    )
+    scripts_dir = skill_dir / "scripts"
+    scripts_dir.mkdir()
+    (scripts_dir / "helper.py").write_text("print('ok')\n", encoding="utf-8")
+
+    archive_path = package_skill.package_skill(skill_dir, tmp_path / "dist")
+
+    assert archive_path == (tmp_path / "dist" / "package-me.skill")
+    assert archive_path.exists()
+    with zipfile.ZipFile(archive_path, "r") as archive:
+        names = set(archive.namelist())
+    assert "package-me/SKILL.md" in names
+    assert "package-me/scripts/helper.py" in names
+
+
+def test_package_skill_rejects_symlink(tmp_path: Path) -> None:
+    skill_dir = tmp_path / "symlink-skill"
+    skill_dir.mkdir()
+    (skill_dir / "SKILL.md").write_text(
+        "---\n"
+        "name: symlink-skill\n"
+        "description: Reject symlinks during packaging.\n"
+        "---\n"
+        "# Skill\n",
+        encoding="utf-8",
+    )
+    scripts_dir = skill_dir / "scripts"
+    scripts_dir.mkdir()
+    target = tmp_path / "outside.txt"
+    target.write_text("secret\n", encoding="utf-8")
+    link = scripts_dir / "outside.txt"
+
+    try:
+        link.symlink_to(target)
+    except (OSError, NotImplementedError):
+        return
+
+    archive_path = package_skill.package_skill(skill_dir, tmp_path / "dist")
+
+    assert archive_path is None
+    assert not (tmp_path / "dist" / "symlink-skill.skill").exists()

tests/test_slack_channel.py

@@ -0,0 +1,90 @@
+from __future__ import annotations
+
+import pytest
+
+from nanobot.bus.events import OutboundMessage
+from nanobot.bus.queue import MessageBus
+from nanobot.channels.slack import SlackChannel
+from nanobot.config.schema import SlackConfig
+
+
+class _FakeAsyncWebClient:
+    def __init__(self) -> None:
+        self.chat_post_calls: list[dict[str, object | None]] = []
+        self.file_upload_calls: list[dict[str, object | None]] = []
+
+    async def chat_postMessage(
+        self,
+        *,
+        channel: str,
+        text: str,
+        thread_ts: str | None = None,
+    ) -> None:
+        self.chat_post_calls.append(
+            {
+                "channel": channel,
+                "text": text,
+                "thread_ts": thread_ts,
+            }
+        )
+
+    async def files_upload_v2(
+        self,
+        *,
+        channel: str,
+        file: str,
+        thread_ts: str | None = None,
+    ) -> None:
+        self.file_upload_calls.append(
+            {
+                "channel": channel,
+                "file": file,
+                "thread_ts": thread_ts,
+            }
+        )
+
+
+@pytest.mark.asyncio
+async def test_send_uses_thread_for_channel_messages() -> None:
+    channel = SlackChannel(SlackConfig(enabled=True), MessageBus())
+    fake_web = _FakeAsyncWebClient()
+    channel._web_client = fake_web
+
+    await channel.send(
+        OutboundMessage(
+            channel="slack",
+            chat_id="C123",
+            content="hello",
+            media=["/tmp/demo.txt"],
+            metadata={"slack": {"thread_ts": "1700000000.000100", "channel_type": "channel"}},
+        )
+    )
+
+    assert len(fake_web.chat_post_calls) == 1
+    assert fake_web.chat_post_calls[0]["text"] == "hello\n"
+    assert fake_web.chat_post_calls[0]["thread_ts"] == "1700000000.000100"
+    assert len(fake_web.file_upload_calls) == 1
+    assert fake_web.file_upload_calls[0]["thread_ts"] == "1700000000.000100"
+
+
+@pytest.mark.asyncio
+async def test_send_omits_thread_for_dm_messages() -> None:
+    channel = SlackChannel(SlackConfig(enabled=True), MessageBus())
+    fake_web = _FakeAsyncWebClient()
+    channel._web_client = fake_web
+
+    await channel.send(
+        OutboundMessage(
+            channel="slack",
+            chat_id="D123",
+            content="hello",
+            media=["/tmp/demo.txt"],
+            metadata={"slack": {"thread_ts": "1700000000.000100", "channel_type": "im"}},
+        )
+    )
+
+    assert len(fake_web.chat_post_calls) == 1
+    assert fake_web.chat_post_calls[0]["text"] == "hello\n"
+    assert fake_web.chat_post_calls[0]["thread_ts"] is None
+    assert len(fake_web.file_upload_calls) == 1
+    assert fake_web.file_upload_calls[0]["thread_ts"] is None

tests/test_task_cancel.py

@@ -165,3 +165,46 @@ class TestSubagentCancellation:
         provider.get_default_model.return_value = "test-model"
         mgr = SubagentManager(provider=provider, workspace=MagicMock(), bus=bus)
         assert await mgr.cancel_by_session("nonexistent") == 0
+
+    @pytest.mark.asyncio
+    async def test_subagent_preserves_reasoning_fields_in_tool_turn(self, monkeypatch, tmp_path):
+        from nanobot.agent.subagent import SubagentManager
+        from nanobot.bus.queue import MessageBus
+        from nanobot.providers.base import LLMResponse, ToolCallRequest
+
+        bus = MessageBus()
+        provider = MagicMock()
+        provider.get_default_model.return_value = "test-model"
+
+        captured_second_call: list[dict] = []
+
+        call_count = {"n": 0}
+
+        async def scripted_chat_with_retry(*, messages, **kwargs):
+            call_count["n"] += 1
+            if call_count["n"] == 1:
+                return LLMResponse(
+                    content="thinking",
+                    tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={})],
+                    reasoning_content="hidden reasoning",
+                    thinking_blocks=[{"type": "thinking", "thinking": "step"}],
+                )
+            captured_second_call[:] = messages
+            return LLMResponse(content="done", tool_calls=[])
+        provider.chat_with_retry = scripted_chat_with_retry
+        mgr = SubagentManager(provider=provider, workspace=tmp_path, bus=bus)
+
+        async def fake_execute(self, name, arguments):
+            return "tool result"
+
+        monkeypatch.setattr("nanobot.agent.tools.registry.ToolRegistry.execute", fake_execute)
+
+        await mgr._run_subagent("sub-1", "do task", "label", {"channel": "test", "chat_id": "c1"})
+
+        assistant_messages = [
+            msg for msg in captured_second_call
+            if msg.get("role") == "assistant" and msg.get("tool_calls")
+        ]
+        assert len(assistant_messages) == 1
+        assert assistant_messages[0]["reasoning_content"] == "hidden reasoning"
+        assert assistant_messages[0]["thinking_blocks"] == [{"type": "thinking", "thinking": "step"}]

tests/test_telegram_channel.py

@@ -0,0 +1,338 @@
+from types import SimpleNamespace
+
+import pytest
+
+from nanobot.bus.events import OutboundMessage
+from nanobot.bus.queue import MessageBus
+from nanobot.channels.telegram import TelegramChannel
+from nanobot.config.schema import TelegramConfig
+
+
+class _FakeHTTPXRequest:
+    instances: list["_FakeHTTPXRequest"] = []
+
+    def __init__(self, **kwargs) -> None:
+        self.kwargs = kwargs
+        self.__class__.instances.append(self)
+
+
+class _FakeUpdater:
+    def __init__(self, on_start_polling) -> None:
+        self._on_start_polling = on_start_polling
+
+    async def start_polling(self, **kwargs) -> None:
+        self._on_start_polling()
+
+
+class _FakeBot:
+    def __init__(self) -> None:
+        self.sent_messages: list[dict] = []
+        self.get_me_calls = 0
+
+    async def get_me(self):
+        self.get_me_calls += 1
+        return SimpleNamespace(id=999, username="nanobot_test")
+
+    async def set_my_commands(self, commands) -> None:
+        self.commands = commands
+
+    async def send_message(self, **kwargs) -> None:
+        self.sent_messages.append(kwargs)
+
+    async def send_chat_action(self, **kwargs) -> None:
+        pass
+
+
+class _FakeApp:
+    def __init__(self, on_start_polling) -> None:
+        self.bot = _FakeBot()
+        self.updater = _FakeUpdater(on_start_polling)
+        self.handlers = []
+        self.error_handlers = []
+
+    def add_error_handler(self, handler) -> None:
+        self.error_handlers.append(handler)
+
+    def add_handler(self, handler) -> None:
+        self.handlers.append(handler)
+
+    async def initialize(self) -> None:
+        pass
+
+    async def start(self) -> None:
+        pass
+
+
+class _FakeBuilder:
+    def __init__(self, app: _FakeApp) -> None:
+        self.app = app
+        self.token_value = None
+        self.request_value = None
+        self.get_updates_request_value = None
+
+    def token(self, token: str):
+        self.token_value = token
+        return self
+
+    def request(self, request):
+        self.request_value = request
+        return self
+
+    def get_updates_request(self, request):
+        self.get_updates_request_value = request
+        return self
+
+    def proxy(self, _proxy):
+        raise AssertionError("builder.proxy should not be called when request is set")
+
+    def get_updates_proxy(self, _proxy):
+        raise AssertionError("builder.get_updates_proxy should not be called when request is set")
+
+    def build(self):
+        return self.app
+
+
+def _make_telegram_update(
+    *,
+    chat_type: str = "group",
+    text: str | None = None,
+    caption: str | None = None,
+    entities=None,
+    caption_entities=None,
+    reply_to_message=None,
+):
+    user = SimpleNamespace(id=12345, username="alice", first_name="Alice")
+    message = SimpleNamespace(
+        chat=SimpleNamespace(type=chat_type, is_forum=False),
+        chat_id=-100123,
+        text=text,
+        caption=caption,
+        entities=entities or [],
+        caption_entities=caption_entities or [],
+        reply_to_message=reply_to_message,
+        photo=None,
+        voice=None,
+        audio=None,
+        document=None,
+        media_group_id=None,
+        message_thread_id=None,
+        message_id=1,
+    )
+    return SimpleNamespace(message=message, effective_user=user)
+
+
+@pytest.mark.asyncio
+async def test_start_uses_request_proxy_without_builder_proxy(monkeypatch) -> None:
+    config = TelegramConfig(
+        enabled=True,
+        token="123:abc",
+        allow_from=["*"],
+        proxy="http://127.0.0.1:7890",
+    )
+    bus = MessageBus()
+    channel = TelegramChannel(config, bus)
+    app = _FakeApp(lambda: setattr(channel, "_running", False))
+    builder = _FakeBuilder(app)
+
+    monkeypatch.setattr("nanobot.channels.telegram.HTTPXRequest", _FakeHTTPXRequest)
+    monkeypatch.setattr(
+        "nanobot.channels.telegram.Application",
+        SimpleNamespace(builder=lambda: builder),
+    )
+
+    await channel.start()
+
+    assert len(_FakeHTTPXRequest.instances) == 1
+    assert _FakeHTTPXRequest.instances[0].kwargs["proxy"] == config.proxy
+    assert builder.request_value is _FakeHTTPXRequest.instances[0]
+    assert builder.get_updates_request_value is _FakeHTTPXRequest.instances[0]
+
+
+def test_derive_topic_session_key_uses_thread_id() -> None:
+    message = SimpleNamespace(
+        chat=SimpleNamespace(type="supergroup"),
+        chat_id=-100123,
+        message_thread_id=42,
+    )
+
+    assert TelegramChannel._derive_topic_session_key(message) == "telegram:-100123:topic:42"
+
+
+def test_get_extension_falls_back_to_original_filename() -> None:
+    channel = TelegramChannel(TelegramConfig(), MessageBus())
+
+    assert channel._get_extension("file", None, "report.pdf") == ".pdf"
+    assert channel._get_extension("file", None, "archive.tar.gz") == ".tar.gz"
+
+
+def test_telegram_group_policy_defaults_to_mention() -> None:
+    assert TelegramConfig().group_policy == "mention"
+
+
+def test_is_allowed_accepts_legacy_telegram_id_username_formats() -> None:
+    channel = TelegramChannel(TelegramConfig(allow_from=["12345", "alice", "67890|bob"]), MessageBus())
+
+    assert channel.is_allowed("12345|carol") is True
+    assert channel.is_allowed("99999|alice") is True
+    assert channel.is_allowed("67890|bob") is True
+
+
+def test_is_allowed_rejects_invalid_legacy_telegram_sender_shapes() -> None:
+    channel = TelegramChannel(TelegramConfig(allow_from=["alice"]), MessageBus())
+
+    assert channel.is_allowed("attacker|alice|extra") is False
+    assert channel.is_allowed("not-a-number|alice") is False
+
+
+@pytest.mark.asyncio
+async def test_send_progress_keeps_message_in_topic() -> None:
+    config = TelegramConfig(enabled=True, token="123:abc", allow_from=["*"])
+    channel = TelegramChannel(config, MessageBus())
+    channel._app = _FakeApp(lambda: None)
+
+    await channel.send(
+        OutboundMessage(
+            channel="telegram",
+            chat_id="123",
+            content="hello",
+            metadata={"_progress": True, "message_thread_id": 42},
+        )
+    )
+
+    assert channel._app.bot.sent_messages[0]["message_thread_id"] == 42
+
+
+@pytest.mark.asyncio
+async def test_send_reply_infers_topic_from_message_id_cache() -> None:
+    config = TelegramConfig(enabled=True, token="123:abc", allow_from=["*"], reply_to_message=True)
+    channel = TelegramChannel(config, MessageBus())
+    channel._app = _FakeApp(lambda: None)
+    channel._message_threads[("123", 10)] = 42
+
+    await channel.send(
+        OutboundMessage(
+            channel="telegram",
+            chat_id="123",
+            content="hello",
+            metadata={"message_id": 10},
+        )
+    )
+
+    assert channel._app.bot.sent_messages[0]["message_thread_id"] == 42
+    assert channel._app.bot.sent_messages[0]["reply_parameters"].message_id == 10
+
+
+@pytest.mark.asyncio
+async def test_group_policy_mention_ignores_unmentioned_group_message() -> None:
+    channel = TelegramChannel(
+        TelegramConfig(enabled=True, token="123:abc", allow_from=["*"], group_policy="mention"),
+        MessageBus(),
+    )
+    channel._app = _FakeApp(lambda: None)
+
+    handled = []
+
+    async def capture_handle(**kwargs) -> None:
+        handled.append(kwargs)
+
+    channel._handle_message = capture_handle
+    channel._start_typing = lambda _chat_id: None
+
+    await channel._on_message(_make_telegram_update(text="hello everyone"), None)
+
+    assert handled == []
+    assert channel._app.bot.get_me_calls == 1
+
+
+@pytest.mark.asyncio
+async def test_group_policy_mention_accepts_text_mention_and_caches_bot_identity() -> None:
+    channel = TelegramChannel(
+        TelegramConfig(enabled=True, token="123:abc", allow_from=["*"], group_policy="mention"),
+        MessageBus(),
+    )
+    channel._app = _FakeApp(lambda: None)
+
+    handled = []
+
+    async def capture_handle(**kwargs) -> None:
+        handled.append(kwargs)
+
+    channel._handle_message = capture_handle
+    channel._start_typing = lambda _chat_id: None
+
+    mention = SimpleNamespace(type="mention", offset=0, length=13)
+    await channel._on_message(_make_telegram_update(text="@nanobot_test hi", entities=[mention]), None)
+    await channel._on_message(_make_telegram_update(text="@nanobot_test again", entities=[mention]), None)
+
+    assert len(handled) == 2
+    assert channel._app.bot.get_me_calls == 1
+
+
+@pytest.mark.asyncio
+async def test_group_policy_mention_accepts_caption_mention() -> None:
+    channel = TelegramChannel(
+        TelegramConfig(enabled=True, token="123:abc", allow_from=["*"], group_policy="mention"),
+        MessageBus(),
+    )
+    channel._app = _FakeApp(lambda: None)
+
+    handled = []
+
+    async def capture_handle(**kwargs) -> None:
+        handled.append(kwargs)
+
+    channel._handle_message = capture_handle
+    channel._start_typing = lambda _chat_id: None
+
+    mention = SimpleNamespace(type="mention", offset=0, length=13)
+    await channel._on_message(
+        _make_telegram_update(caption="@nanobot_test photo", caption_entities=[mention]),
+        None,
+    )
+
+    assert len(handled) == 1
+    assert handled[0]["content"] == "@nanobot_test photo"
+
+
+@pytest.mark.asyncio
+async def test_group_policy_mention_accepts_reply_to_bot() -> None:
+    channel = TelegramChannel(
+        TelegramConfig(enabled=True, token="123:abc", allow_from=["*"], group_policy="mention"),
+        MessageBus(),
+    )
+    channel._app = _FakeApp(lambda: None)
+
+    handled = []
+
+    async def capture_handle(**kwargs) -> None:
+        handled.append(kwargs)
+
+    channel._handle_message = capture_handle
+    channel._start_typing = lambda _chat_id: None
+
+    reply = SimpleNamespace(from_user=SimpleNamespace(id=999))
+    await channel._on_message(_make_telegram_update(text="reply", reply_to_message=reply), None)
+
+    assert len(handled) == 1
+
+
+@pytest.mark.asyncio
+async def test_group_policy_open_accepts_plain_group_message() -> None:
+    channel = TelegramChannel(
+        TelegramConfig(enabled=True, token="123:abc", allow_from=["*"], group_policy="open"),
+        MessageBus(),
+    )
+    channel._app = _FakeApp(lambda: None)
+
+    handled = []
+
+    async def capture_handle(**kwargs) -> None:
+        handled.append(kwargs)
+
+    channel._handle_message = capture_handle
+    channel._start_typing = lambda _chat_id: None
+
+    await channel._on_message(_make_telegram_update(text="hello group"), None)
+
+    assert len(handled) == 1
+    assert channel._app.bot.get_me_calls == 0

tests/test_tool_validation.py

@@ -106,3 +106,301 @@ def test_exec_extract_absolute_paths_captures_posix_absolute_paths() -> None:
     paths = ExecTool._extract_absolute_paths(cmd)
     assert "/tmp/data.txt" in paths
     assert "/tmp/out.txt" in paths
+
+
+def test_exec_extract_absolute_paths_captures_home_paths() -> None:
+    cmd = "cat ~/.nanobot/config.json > ~/out.txt"
+    paths = ExecTool._extract_absolute_paths(cmd)
+    assert "~/.nanobot/config.json" in paths
+    assert "~/out.txt" in paths
+
+
+def test_exec_extract_absolute_paths_captures_quoted_paths() -> None:
+    cmd = 'cat "/tmp/data.txt" "~/.nanobot/config.json"'
+    paths = ExecTool._extract_absolute_paths(cmd)
+    assert "/tmp/data.txt" in paths
+    assert "~/.nanobot/config.json" in paths
+
+
+def test_exec_guard_blocks_home_path_outside_workspace(tmp_path) -> None:
+    tool = ExecTool(restrict_to_workspace=True)
+    error = tool._guard_command("cat ~/.nanobot/config.json", str(tmp_path))
+    assert error == "Error: Command blocked by safety guard (path outside working dir)"
+
+
+def test_exec_guard_blocks_quoted_home_path_outside_workspace(tmp_path) -> None:
+    tool = ExecTool(restrict_to_workspace=True)
+    error = tool._guard_command('cat "~/.nanobot/config.json"', str(tmp_path))
+    assert error == "Error: Command blocked by safety guard (path outside working dir)"
+
+
+# --- cast_params tests ---
+
+
+class CastTestTool(Tool):
+    """Minimal tool for testing cast_params."""
+
+    def __init__(self, schema: dict[str, Any]) -> None:
+        self._schema = schema
+
+    @property
+    def name(self) -> str:
+        return "cast_test"
+
+    @property
+    def description(self) -> str:
+        return "test tool for casting"
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return self._schema
+
+    async def execute(self, **kwargs: Any) -> str:
+        return "ok"
+
+
+def test_cast_params_string_to_int() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"count": {"type": "integer"}},
+        }
+    )
+    result = tool.cast_params({"count": "42"})
+    assert result["count"] == 42
+    assert isinstance(result["count"], int)
+
+
+def test_cast_params_string_to_number() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"rate": {"type": "number"}},
+        }
+    )
+    result = tool.cast_params({"rate": "3.14"})
+    assert result["rate"] == 3.14
+    assert isinstance(result["rate"], float)
+
+
+def test_cast_params_string_to_bool() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"enabled": {"type": "boolean"}},
+        }
+    )
+    assert tool.cast_params({"enabled": "true"})["enabled"] is True
+    assert tool.cast_params({"enabled": "false"})["enabled"] is False
+    assert tool.cast_params({"enabled": "1"})["enabled"] is True
+
+
+def test_cast_params_array_items() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {
+                "nums": {"type": "array", "items": {"type": "integer"}},
+            },
+        }
+    )
+    result = tool.cast_params({"nums": ["1", "2", "3"]})
+    assert result["nums"] == [1, 2, 3]
+
+
+def test_cast_params_nested_object() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {
+                "config": {
+                    "type": "object",
+                    "properties": {
+                        "port": {"type": "integer"},
+                        "debug": {"type": "boolean"},
+                    },
+                },
+            },
+        }
+    )
+    result = tool.cast_params({"config": {"port": "8080", "debug": "true"}})
+    assert result["config"]["port"] == 8080
+    assert result["config"]["debug"] is True
+
+
+def test_cast_params_bool_not_cast_to_int() -> None:
+    """Booleans should not be silently cast to integers."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"count": {"type": "integer"}},
+        }
+    )
+    result = tool.cast_params({"count": True})
+    assert result["count"] is True
+    errors = tool.validate_params(result)
+    assert any("count should be integer" in e for e in errors)
+
+
+def test_cast_params_preserves_empty_string() -> None:
+    """Empty strings should be preserved for string type."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"name": {"type": "string"}},
+        }
+    )
+    result = tool.cast_params({"name": ""})
+    assert result["name"] == ""
+
+
+def test_cast_params_bool_string_false() -> None:
+    """Test that 'false', '0', 'no' strings convert to False."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"flag": {"type": "boolean"}},
+        }
+    )
+    assert tool.cast_params({"flag": "false"})["flag"] is False
+    assert tool.cast_params({"flag": "False"})["flag"] is False
+    assert tool.cast_params({"flag": "0"})["flag"] is False
+    assert tool.cast_params({"flag": "no"})["flag"] is False
+    assert tool.cast_params({"flag": "NO"})["flag"] is False
+
+
+def test_cast_params_bool_string_invalid() -> None:
+    """Invalid boolean strings should not be cast."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"flag": {"type": "boolean"}},
+        }
+    )
+    # Invalid strings should be preserved (validation will catch them)
+    result = tool.cast_params({"flag": "random"})
+    assert result["flag"] == "random"
+    result = tool.cast_params({"flag": "maybe"})
+    assert result["flag"] == "maybe"
+
+
+def test_cast_params_invalid_string_to_int() -> None:
+    """Invalid strings should not be cast to integer."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"count": {"type": "integer"}},
+        }
+    )
+    result = tool.cast_params({"count": "abc"})
+    assert result["count"] == "abc"  # Original value preserved
+    result = tool.cast_params({"count": "12.5.7"})
+    assert result["count"] == "12.5.7"
+
+
+def test_cast_params_invalid_string_to_number() -> None:
+    """Invalid strings should not be cast to number."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"rate": {"type": "number"}},
+        }
+    )
+    result = tool.cast_params({"rate": "not_a_number"})
+    assert result["rate"] == "not_a_number"
+
+
+def test_validate_params_bool_not_accepted_as_number() -> None:
+    """Booleans should not pass number validation."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"rate": {"type": "number"}},
+        }
+    )
+    errors = tool.validate_params({"rate": False})
+    assert any("rate should be number" in e for e in errors)
+
+
+def test_cast_params_none_values() -> None:
+    """Test None handling for different types."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {
+                "name": {"type": "string"},
+                "count": {"type": "integer"},
+                "items": {"type": "array"},
+                "config": {"type": "object"},
+            },
+        }
+    )
+    result = tool.cast_params(
+        {
+            "name": None,
+            "count": None,
+            "items": None,
+            "config": None,
+        }
+    )
+    # None should be preserved for all types
+    assert result["name"] is None
+    assert result["count"] is None
+    assert result["items"] is None
+    assert result["config"] is None
+
+
+def test_cast_params_single_value_not_auto_wrapped_to_array() -> None:
+    """Single values should NOT be automatically wrapped into arrays."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"items": {"type": "array"}},
+        }
+    )
+    # Non-array values should be preserved (validation will catch them)
+    result = tool.cast_params({"items": 5})
+    assert result["items"] == 5  # Not wrapped to [5]
+    result = tool.cast_params({"items": "text"})
+    assert result["items"] == "text"  # Not wrapped to ["text"]
+
+
+# --- ExecTool enhancement tests ---
+
+
+async def test_exec_always_returns_exit_code() -> None:
+    """Exit code should appear in output even on success (exit 0)."""
+    tool = ExecTool()
+    result = await tool.execute(command="echo hello")
+    assert "Exit code: 0" in result
+    assert "hello" in result
+
+
+async def test_exec_head_tail_truncation() -> None:
+    """Long output should preserve both head and tail."""
+    tool = ExecTool()
+    # Generate output that exceeds _MAX_OUTPUT
+    big = "A" * 6000 + "\n" + "B" * 6000
+    result = await tool.execute(command=f"echo '{big}'")
+    assert "chars truncated" in result
+    # Head portion should start with As
+    assert result.startswith("A")
+    # Tail portion should end with the exit code which comes after Bs
+    assert "Exit code:" in result
+
+
+async def test_exec_timeout_parameter() -> None:
+    """LLM-supplied timeout should override the constructor default."""
+    tool = ExecTool(timeout=60)
+    # A very short timeout should cause the command to be killed
+    result = await tool.execute(command="sleep 10", timeout=1)
+    assert "timed out" in result
+    assert "1 seconds" in result
+
+
+async def test_exec_timeout_capped_at_max() -> None:
+    """Timeout values above _MAX_TIMEOUT should be clamped."""
+    tool = ExecTool()
+    # Should not raise — just clamp to 600
+    result = await tool.execute(command="echo ok", timeout=9999)
+    assert "Exit code: 0" in result