Three tools with basic schemas and minimal descriptions. All tools lack parameter descriptions, critical gap per pattern:tool-description. Schemas present but sparse: no enums, no constraints, no output documentation. Tool names follow verb_noun convention (google_trends_*) but descriptions are generic (10-50 chars, well below 50-200 char baseline for LLM optimization). No error handling guidance, no pagination support despite API returning lists. Parameters accept language/country codes but lack format constraints or examples of valid values.

• Add 50-150 character descriptions to each tool explaining WHAT it does, WHEN to use it, and WHAT it returns. Example: 'Get currently trending topics from Google Trends for a specific country and language. Returns a list of trending search terms ranked by popularity. Use this to discover what users are searching for right now.'
• Add descriptions to all parameters. For 'language': 'ISO 639-1 language code (e.g., en, fr, de, es). Defaults to en.' For 'country': 'ISO 3166-1 alpha-2 country code (e.g., US, GB, DE, FR). Defaults to US.'
• Document output schemas in tool descriptions or via a separate schema field. Example: 'Returns {status: string, timestamp: ISO8601, api_available: boolean}' or 'Returns {questions: [{query: string, related_queries: string[]}], total: number}'
• Add enum constraints for 'language' and 'country' parameters in the input schema. Enumerate valid codes (at least common ones: en, fr, de, es, it, pt, ja, zh, ko; US, GB, DE, FR, IT, ES, JP, CN, KR, etc.) to prevent invalid API calls.
• Enhance error responses with recovery guidance. Instead of 'Error: Invalid country code', return 'Invalid country code: got "XX". Must be ISO 3166-1 alpha-2 (e.g., US, GB, DE). Call google_trends_status to verify API availability.' This guides the LLM's next action.