Single tool 'get_docs' has a verb-based name (good), but the description is overly long (194 chars) and includes example values ('Chroma DB', 'LangChain') that LLMs may reuse literally. Input schema is present with types and descriptions, but lacks enums for the 'library' parameter despite supporting only 3 known values (langchain, llama-index, openai). No output schema is documented, the tool returns unstructured text rather than structured objects. Error handling returns plain strings instead of actionable recovery guidance. The tool combines search + fetch operations, violating single-responsibility principle.

• Add enum constraint to 'library' parameter: {"type": "string", "enum": ["langchain", "llama-index", "openai"], "description": "The documentation library to search in"}
• Document output schema: return {"results": [{"url": string, "title": string, "content": string, "source": string}]} instead of raw text concatenation
• Remove example values from description. Replace 'e.g. Chroma DB' with constraint text: 'The search query (2-100 characters, alphanumeric + spaces)'
• Implement structured error responses with recovery hints: {"error": "library_not_supported", "message": "Library 'X' not found", "valid_options": ["langchain", "llama-index", "openai"]}
• Consider splitting into two tools: search_docs (returns paginated results with URLs) and fetch_doc_content (retrieves full page text for a given URL)