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 mentions what data is returned ('total awards and per-capita spending'), but does not cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or data freshness. For a tool with no annotations, this leaves significant behavioral gaps, though it at least describes the output content.

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 extremely concise and front-loaded: a single sentence that directly states the tool's purpose and output. Every word earns its place with no redundancy or fluff, making it efficient and easy to parse quickly.

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 output but lacks details on behavioral traits, error handling, or data sources. With no output schema, it should ideally describe return values more thoroughly, but the mention of 'total awards and per-capita spending' provides some context, keeping it at a baseline level.

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 description does not add any parameter-specific information beyond what is already in the input schema, which has 100% schema description coverage. The schema fully documents both parameters ('state' and 'fiscal_year'), so the description's lack of param details is acceptable, resulting in the baseline score of 3 for adequate coverage via schema alone.

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 federal spending by state or territory. Shows total awards and per-capita spending.' It specifies the verb ('Get'), resource ('federal spending'), and scope ('by state or territory'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'usa_spending_by_agency' or 'usa_spending_by_recipient', which prevents a score of 5.

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 implies usage for retrieving federal spending data by state/territory, but does not provide explicit guidance on when to use this tool versus alternatives like 'usa_spending_by_agency'. The input schema hints at usage (e.g., omitting 'state' for all states), but the description itself lacks clear when/when-not instructions or named alternatives, leaving usage somewhat inferred.

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