Four tools with basic schemas and minimal descriptions. All tools have input schemas with typed parameters (a, b, query, location), but descriptions are extremely short (10-50 chars, well below the 194-char baseline). No output schemas documented. No error handling guidance. Math tools (add, multiply) are trivial; search and weather tools call external APIs but lack retry logic, timeout handling, or actionable error messages. No parameter validation, no enum constraints, no pagination for list results. Security issue: OpenWeatherMap API key hardcoded in source code (weather_server.py line 11). No tool annotations (readOnlyHint, destructiveHint, idempotentHint). Composition is reasonable (each tool does one thing), but descriptions are too terse for LLM selection.

• Move OpenWeatherMap API key to environment variable (os.getenv('OPENWEATHERMAP_API_KEY')) and remove from source. Use server-side secret injection pattern.
• Expand tool descriptions to 100-200 chars. Example for search: 'Search the web using SerpAPI. Returns the top answer or snippet. Use when the user asks for current information, news, or facts not in your training data. Requires SERPAPI_API_KEY environment variable.'
• Document output schemas for search() and get_weather(). Example: search returns {"result": string, "source": string}; get_weather returns {"location": string, "weather": string, "temperature": number, "unit": string}.
• Add error handling guidance. Example: 'If location not found, suggest similar location names. If API rate limit hit, advise user to retry in 60 seconds.' Categorize errors as retryable vs user-fixable.
• Add tool annotations via FastMCP decorator or schema metadata. Mark all tools with readOnlyHint=true since they have no side effects. This enables agents to safely retry on transient failures.