Here's an example of how my agent handles this: Gathering context for user request... Context gathering - Attempting to answer question via LLM: Are there exi

Here's an example of how my agent handles this: Gathering context for user request... Context gathering - Attempting to answer question via LLM: Are there existing Conversation classes in the ecosystem this should extend? Context gathering - LLM provided answer: "No" Context gathering - Attempting to answer question via LLM: How should model selection work when continuing a previous conversation? Context gathering - LLM answer was UNKNOWN, asking user. Asking user: How should model selection work when continuing a previous conversation? Context gathering - received user response to question: "How should model selection work when continuing a previous conversation?" Context gathering - finished processing all user questions Context gathering - processing command executions... Context gathering - executing command: sqlite3 $(find . -name llm_conversations.db) .tables Context gathering - command execution completed Context gathering - executing command: grep -r Conversation tests/ Context gathering - command execution completed Context gathering - executing command: grep -h conversation_id *py Context gathering - command execution completed Context gathering - finished processing all commands Analyzing task complexity and requirements... DEBUG: reasoning_model: openrouter/google/gemini-2.5-pro-preview-03-25 Task classified as coding (confidence: 1.0) Task difficulty score: 98.01339999999999/100 Selected primary reasoning model: claude-3.7-sonnet get_reasoning_assistance:[:214: integer expression expected: 98.01339999999999 Reasoning assistance completed in 39 seconds Calling LLM with model: claude-3.7-sonnet