8 tools with basic schemas and descriptions, but significant gaps in parameter documentation and output schema clarity. All tools are READ_ONLY (good for safety), but descriptions are generic (avg ~40 chars, well below 194-char baseline). Parameter descriptions exist but lack constraints (enums, ranges, formats). Output schemas inferred from Pydantic models in source but not explicitly documented in tool definitions. No error handling guidance. Tool names follow verb_noun pattern (positive), but some are generic ('Get Video Info' vs 'Get Video Metadata'). Composition is reasonable, tools are single-purpose and chainable via IDs.

• Expand tool descriptions to 100 - 200 chars. Example: 'Get Video Info' → 'Retrieve detailed metadata for a YouTube video including title, description, view count, likes, duration, and tags. Requires a valid 11-character video ID. Use extract_video_id() to parse URLs.'
• Convert free-form string parameters to enums. For 'order' param, define: enum=['date', 'rating', 'relevance', 'title', 'videoCount', 'viewCount'] with description 'Sort results by this field (default: relevance).'
• Document output schemas explicitly in tool definitions. Add a 'returns' field or JSON Schema object showing VideoInfo structure: {video_id, video_title, channel_id, view_count, like_count, duration, tags, ...}.
• Add error handling to all tools. Catch API exceptions and return structured errors: {'error': 'Video not found', 'suggestion': 'Try search_videos() with a keyword to find the correct video ID.'}
• Clarify pagination in search tools. Add to descriptions: 'Returns up to max_results items (default 50). If more results exist, use the next_page_token from the response to fetch the next batch.'