fix(subagent): preserve reasoning fields across tool turns

Share assistant message construction between the main agent and subagents, and add a regression test to keep reasoning_content and thinking_blocks in follow-up tool rounds.

nanobot/agent/context.py

@@ -10,7 +10,7 @@ from typing import Any
 
 from nanobot.agent.memory import MemoryStore
 from nanobot.agent.skills import SkillsLoader
-from nanobot.utils.helpers import detect_image_mime
+from nanobot.utils.helpers import build_assistant_message, detect_image_mime
 
 
 class ContextBuilder:
@@ -182,12 +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/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:
@@ -133,7 +134,6 @@ class SubagentManager:
                 )
 
                 if response.has_tool_calls:
-                    # Add assistant message with tool calls
                     tool_call_dicts = [
                         {
                             "id": tc.id,
@@ -145,19 +145,12 @@ class SubagentManager:
                         }
                         for tc in response.tool_calls
                     ]
-                    assistant_msg: dict[str, Any] = {
+                    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,
-                    # Preserve reasoning_content for providers that require it
+                    ))
-                    # (e.g. Deepseek Reasoner mandates this field on every
-                    # assistant message when thinking mode is active).
-                    if response.reasoning_content is not None:
-                        assistant_msg["reasoning_content"] = response.reasoning_content
-                    if response.thinking_blocks:
-                        assistant_msg["thinking_blocks"] = response.thinking_blocks
-                    messages.append(assistant_msg)
 
                     # Execute tools
                     for tool_call in response.tool_calls:

nanobot/utils/helpers.py

@@ -72,6 +72,23 @@ def split_message(content: str, max_len: int = 2000) -> list[str]:
     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,

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"}]