US Government Open Data MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the search is case-insensitive and covers specific fields (name, table name, endpoint path, description), which is useful behavioral context. However, it lacks details on response format, pagination, rate limits, or error handling, leaving gaps for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the purpose and key details (scope, fields searched). Every word earns its place with no redundancy or fluff, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (search across many datasets), no annotations, and no output schema, the description is reasonably complete. It covers purpose, scope, and search fields, but lacks details on output structure or behavioral constraints like performance or limits, which would be helpful for full completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'query' parameter well-documented in the schema itself. The description adds no additional parameter semantics beyond what the schema provides, such as search syntax or examples. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the action ('Search'), the target resource ('Treasury Fiscal Data datasets and endpoints'), and the scope ('across all 53 datasets (181 endpoints)'). It clearly distinguishes this from sibling tools like 'list_datasets' (which likely lists without search) and 'query_fiscal_data' (which likely queries specific datasets).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: to search datasets/endpoints by keyword across the entire Treasury Fiscal Data collection. However, it does not explicitly state when not to use it (e.g., for querying specific dataset data) or name alternative tools like 'list_datasets' or 'query_fiscal_data', though these can be inferred from sibling names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.