This server has significant definition quality gaps. Both tools are registered via the fastmcp decorator pattern and have basic descriptions, but parameter descriptions are incomplete or missing, input schemas are not fully visible in the provided source, and there is no documented output schema. The tool names follow verb_noun convention (search_*), which is positive, but the parameter documentation falls short of production standards. The descriptions are moderate in length (tool 1: ~200 chars, tool 2: ~280 chars) but contain procedural guidance rather than LLM-optimized clarity. Parameters like 'ctx' (Context type) and 'inventory' (dict[str, Any]) lack proper type hints and constraints in the visible schema.

• Add explicit parameter descriptions for 'ctx' on both tools. Since 'ctx' is injected by fastmcp, either document it as optional (and hidden from LLM schema) or refactor to not expose it as a parameter the LLM sees.
• Document the output schema for both tools. Specify: field names, types, whether arrays are paginated, total count if applicable, and include the inventory keys/dataset IDs needed for chaining to datajson_search_datasets.
• Rewrite tool descriptions to state WHAT each tool returns and WHEN to use it. Example for datajson_search_inventory: 'Searches the Medicaid data inventory using BM25 ranking. Returns up to k dataset summaries ranked by relevance to your query. Use this to discover relevant datasets before calling datajson_search_datasets for column-level details.'
• Add constraints to numeric parameters. Example: 'k: number of results to return (1-100, default 10). Will return fewer if <k datasets have positive scores.'
• Define input validation rules and error responses. Document: 'If query is empty, returns empty dict. If limit exceeds available datasets, returns all available. If inventory is malformed, returns error: {error: string, recovery: string}'.
• Remove dependency injection of Context from the tool signature if possible. If 'ctx' is needed for lifespan/session data (BM25 index, inventory), document this as a server-internal detail and do not expose it as an LLM-facing parameter. Use fastmcp's lifecycle hooks instead.
• Add pagination guidance. If many datasets match, specify how the agent should iterate (e.g., via offset/limit or cursor-based pagination in future versions).