fix(memory): reserve completion headroom for consolidation

Trigger token consolidation before prompt usage reaches the full context window so response tokens and tokenizer estimation drift still fit safely within the model budget.

Made-with: Cursor

tests/test_loop_consolidation_tokens.py

@@ -9,8 +9,10 @@ from nanobot.providers.base import LLMResponse
 
 
 def _make_loop(tmp_path, *, estimated_tokens: int, context_window_tokens: int) -> AgentLoop:
+    from nanobot.providers.base import GenerationSettings
     provider = MagicMock()
     provider.get_default_model.return_value = "test-model"
+    provider.generation = GenerationSettings(max_tokens=0)
     provider.estimate_prompt_tokens.return_value = (estimated_tokens, "test-counter")
     _response = LLMResponse(content="ok", tool_calls=[])
     provider.chat_with_retry = AsyncMock(return_value=_response)
@@ -24,6 +26,7 @@ def _make_loop(tmp_path, *, estimated_tokens: int, context_window_tokens: int) -
         context_window_tokens=context_window_tokens,
     )
     loop.tools.get_definitions = MagicMock(return_value=[])
+    loop.memory_consolidator._SAFETY_BUFFER = 0
     return loop