Five tools with clear naming (verb_noun pattern) and reasonable descriptions (100-200 chars). All tools have input schemas with typed parameters and descriptions. However, output schemas are not documented in the source code provided, and parameter descriptions lack specificity around constraints, formats, and error recovery. The save_trace and save_knowledge tools accept JSON strings as parameters, which is error-prone and forces LLMs to construct JSON manually. No tool annotations (readOnlyHint/destructiveHint) are present despite clear risk classifications. Error handling guidance is absent.

• Replace trace_json and properties_json string parameters with structured objects. Define a TraceInput type with fields: source (enum), intent (string), steps (array of step objects), outcome (object with status and summary), context (object). This matches the chat-data-model and eliminates JSON construction errors.
• Document output schemas for all tools. Specify which fields are returned, their types, and which IDs/references enable chaining. E.g., does search() return entity_id, entity_type, domain? Does get_context() return trace_ids for follow-up calls?
• Add tool annotations to the MCP protocol registration. Mark save_trace and save_knowledge with destructiveHint=true; mark get_context, search, recent_activity with readOnlyHint=true. This enables clients to enforce safety policies.
• Enhance parameter descriptions with constraints and examples. E.g., 'limit: Maximum results to return (1 - 100, default 20). Larger limits may timeout.' 'domain: Optional scope filter (e.g., "backend", "platform"). If omitted, searches all domains.'
• Add error recovery guidance to tool descriptions. E.g., 'If save_trace fails with "invalid_json", ensure trace_json is valid JSON. If it fails with "permission_denied", verify the agent has write access to the domain.'

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry