Three tools with basic schemas and descriptions, but significant gaps in parameter documentation and output schema clarity. All tools have descriptions (10-20 chars baseline met), but lack depth on WHEN to use them and what they return. Parameter descriptions are minimal, 'Programming language filter' doesn't explain valid formats, ranges, or examples. No output schemas documented. Error handling returns JSON but lacks recovery guidance. Tools follow verb_noun naming (getTrending*) but descriptions are generic and don't differentiate use cases.

• Document output schemas for all three tools. Publish the structure of repositories array (fields: name, url, description, language, stars, starsUrl, forks, forksUrl, starsToday, starsTodayText, contributors), metadata object, and statistics object so LLMs know what to extract.
• Replace example-based parameter descriptions with formal constraints. Convert 'e.g.: python, javascript, typescript, rust, go, java, c, c++, c#' to an enum or regex pattern. Same for spokenLanguageCode, declare valid ISO 639-1 codes or provide an enum.
• Expand tool descriptions to clarify use cases. E.g., 'getTrendingMetadata: Fetch page title, description, and applied filters. Call this first to understand what filters are active before fetching repositories.' This helps LLMs choose the right tool.
• Add error recovery guidance. When a language or spoken language code is invalid, return 'Invalid language: got "xyz". Valid options: python, javascript, typescript, rust, go, java, c, c++, c#' so the LLM can self-correct.
• Consider adding a limit/pagination parameter to getTrendingRepositories. If the API returns 100+ repos, cap results at 20-50 and offer a next_cursor or offset parameter to avoid context window exhaustion.