Five tools with complete schemas and descriptions, but significant quality gaps. All tools have descriptions (10-50 chars, below the 50-200 char baseline for LLM optimization) and input schemas are present. However, descriptions are minimal and lack actionable context. Parameter descriptions are sparse or missing entirely. No output schemas documented. Error handling is absent, no guidance on what to do if synthesis fails or provider is unavailable. Tools follow a consistent naming pattern (notify_*) but descriptions are Japanese-only, limiting accessibility. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite all being read-only operations.

• Expand all descriptions to 50-200 characters with clear WHAT/WHEN/WHY. Example: 'notify_complete: Play a completion sound and speak a message (default: "Task completed"). Use when a long-running operation finishes to alert the user. Returns success status and message played.'
• Document output schemas for all tools. Example: notify_list_providers should return {providers: [{name: string, available: boolean, speakers?: number[]}], default: string}.
• Add parameter descriptions for 'message' (optional, max 500 chars, defaults to locale-specific message) and 'speaker' (VOICEVOX: 0-100+, other providers: string ID; see notify_list_providers for valid values).
• Add error handling with recovery guidance. Example: 'If synthesis fails, check provider availability with notify_test. If unavailable, try switching provider via config or notify_list_providers.'
• Translate descriptions to English or provide bilingual descriptions. Japanese-only descriptions block non-Japanese LLMs and users from understanding tool purpose.