Three well-named, read-only tools with complete input schemas and clear descriptions. search_podcast has excellent parameter documentation (query, k with range 1-20, mode with enum). list_episodes and episode_detail are simpler but properly defined. Output schemas are documented in descriptions. No security issues (read-only, no secrets). Main gaps: no error handling guidance (e.g., what if episode_id doesn't exist?), no pagination support for search_podcast results, and descriptions could be more concise (search_podcast is 380+ chars, exceeds 200-char LLM-optimized baseline). Tool composition is sound, each does one thing. Per-tool scores: search_podcast 75, list_episodes 70, episode_detail 70.

• Trim search_podcast description to ~150 chars: 'Search podcast archive by natural language query. Returns ranked passages with timestamps, episode IDs, and citation tags. Supports BM25 (raw/stemmed) and dense vector search modes.'
• Add error handling to search_podcast: validate k in [1,20], handle empty query gracefully, document what 'score' field represents (BM25 relevance, cosine similarity, etc.).
• Enhance episode_detail error response: return available episode_ids on 404. E.g., 'Unknown episode_id: ep99. Available: ep01, ep02, ep03, ...'
• Add pagination to search_podcast if corpus grows: accept limit (default 5, max 20) and offset; return total_count and has_more flag.
• Document output schemas formally in code comments or docstrings. E.g., 'Returns: {query: str, mode: str, count: int, results: [{chunk_id, episode_id, timestamp, source, citation, text, score}]}'.