Single tool 'get_weather' has a basic description (23 chars) and minimal input schema. The description lacks context on when/why to use the tool, what it returns, or any prerequisites. Input schema defines 'city' parameter but provides no type constraint (string type is present but no description for the parameter itself). No output schema documented. No error handling guidance. Tool naming follows verb_noun convention but descriptions fall well below the 50-200 char baseline for LLM-optimized tools. Framework is clean but tool definitions are underdeveloped.

• Expand tool description to 80-150 chars: 'Get current weather conditions (temperature, condition) for a city. Returns real-time data. Call this when the user asks about weather in a specific location.'
• Add description to 'city' parameter: 'The name of the city (e.g., New York, London). Use the city name, not a country code or coordinates.'
• Document output schema in the tool metadata: { temp: string, condition: string, city: string } with descriptions for each field.
• Add error handling: catch 'city not found' and return 'City not found. Try a major city name (e.g., New York, London, Tokyo).' to guide the LLM.
• Consider adding optional parameters like 'units' (celsius|fahrenheit) with enum constraint to make the tool more flexible.