Server has 4 tools with basic schemas and descriptions, but significant quality gaps. All tools have input schemas with type definitions and descriptions present, meeting minimum requirements. However, descriptions are minimal (10-20 chars), parameter descriptions lack detail about constraints/formats, and output schemas are undocumented. No error handling guidance, no parameter validation rules, and no indication of idempotency or side effects. Tools operate on in-memory state with no persistence, limiting production utility. Naming follows verb_noun pattern (set_, update_, log_, compress_) which is good, but descriptions are too terse to guide LLM selection effectively.

• Expand tool descriptions to 50-200 characters. Example: 'set_core_objective: Define the high-level goal guiding all tasks. Call this first to establish context. Replaces any previous objective.' This explains WHAT, WHEN, and WHAT IT REPLACES.
• Add structured output schemas. Instead of returning 'updated successfully', return {"status": "success", "timestamp": "2024-01-15T10:30:00Z", "objective": "<new value>"}. This enables downstream tool chaining and LLM reasoning.
• Document parameter constraints in descriptions. E.g., 'objective (string, 10-500 chars): The core goal. Should be specific and measurable. E.g., "Complete Q1 project roadmap by March 31."', but use enum/pattern in schema, not examples in text.
• Add error handling with recovery hints. E.g., if compress_history receives an empty summary, return {"error": "Summary cannot be empty. Provide a brief recap of recent actions before clearing history."}
• Declare tool side effects and idempotency. Add to descriptions: 'DESTRUCTIVE: Clears recent_actions. IDEMPOTENT: Safe to retry with same summary.' This guides agent retry logic.