Server has 11 tools with mostly complete schemas and descriptions in Chinese. Naming follows verb_noun pattern (remember, recall, forget, etc.). Descriptions are detailed but lengthy (200-400+ chars, exceeding the 10-1024 baseline sweet spot of 50-200). All tools have input schemas with types. However, output schemas are not documented in the source code, responses are inferred from implementation. Error handling is minimal; no recovery guidance or error classification. Security: no secrets exposed as params (good), but no permission gates or audit trail logging visible. Tool composition is sound (each does one thing), but some tools could be better scoped (e.g., who_am_i mixes identity + stats).

• Document output schemas for all tools. For recall/search_memories, specify: { memories: [{ id, title, category, tags, updated_at, links: [{ id, title, category }] }], total_count, next_cursor? }. For journal_entry, specify: { id, agent, timestamp, user, question, answer_summary, key_points, open_question }.
• Trim descriptions to 50-200 chars. Remove implementation details (SQLite, Chroma, Markdown). Focus on user intent: 'recall: Retrieve memories matching a query using semantic + keyword search. Call when user asks about past decisions or lessons learned.'
• Add error handling with recovery guidance. E.g., remember() should return: { success: false, error: 'Vector embedding failed', recovery: 'Memory stored in SQLite but not indexed. Try recall() with keywords.' }. Categorize errors as retryable, user-fixable, or fatal.
• Split who_am_i into get_agent_identity (returns agent, user, project_root) and get_memory_stats (returns counts per category). Simpler, more composable.
• Add a confirm_forget tool or dry_run parameter to forget. E.g., forget(id, dry_run=true) returns what would be deleted; agent confirms before calling forget(id, dry_run=false).