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 of behavioral disclosure. It states the tool retrieves data ('Get an overview'), implying a read-only operation, but does not specify response format, pagination, rate limits, authentication needs, or error handling. For a tool with no annotations, this is insufficient to inform the agent about key behavioral traits.

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 concise and front-loaded, with the core purpose stated in the first sentence and supplementary details (common codes) in the second. There is no wasted text, and it efficiently communicates essential information, though it could be slightly more structured (e.g., separating usage notes).

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 (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameter hints but lacks details on output structure, error cases, or integration with sibling tools. Without annotations or an output schema, the agent is left with gaps in understanding the full context of use.

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?

Schema description coverage is 100%, so the schema already documents both parameters ('agency_code' and 'fiscal_year') with descriptions and examples. The description adds a list of common agency codes, which partially overlaps with the schema's examples but provides additional context. However, it does not explain the meaning or implications of these parameters beyond what the schema offers, resulting in a baseline score.

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 clearly states the tool's purpose: 'Get an overview of a federal agency's spending, including budgetary resources and obligations.' This specifies the verb ('Get'), resource ('federal agency's spending'), and scope ('budgetary resources and obligations'). However, it does not explicitly differentiate from sibling tools like 'usa_spending_by_agency' or 'usa_spending_over_time', which likely provide different views of spending data, so it falls short of a perfect score.

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 no guidance on when to use this tool versus alternatives. It lists common agency codes, but this is parameter information, not usage context. There is no mention of prerequisites, when-not-to-use scenarios, or comparisons to sibling tools, leaving the agent without clear selection criteria.

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