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 mentions filtering and award type groups/codes, but fails to disclose critical behavioral traits such as pagination behavior (implied by 'limit' and 'page' parameters but not explained), rate limits, authentication needs, or what the output looks like (e.g., format, fields). For a search tool with 12 parameters and no output schema, this is a significant gap.

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 appropriately sized and front-loaded, with the first sentence stating the core purpose and key filters. The second sentence adds necessary detail on award type mappings without redundancy. However, it could be slightly more structured by separating usage notes from parameter details.

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 complexity (12 parameters, no annotations, no output schema), the description is incomplete. It covers the purpose and some parameter context but lacks essential behavioral details like output format, pagination behavior, error handling, or rate limits. For a search tool in a data-rich context, this leaves significant gaps for an AI agent.

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 all 12 parameters thoroughly. The description adds minimal value beyond the schema by listing filterable fields and providing award type group/code mappings, but does not elaborate on parameter interactions, defaults, or constraints beyond what's in the schema descriptions. Baseline 3 is appropriate when 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 clearly states the tool's purpose with specific verbs ('Search federal spending awards') and resources ('contracts, grants, loans, direct payments'), and distinguishes it from siblings by focusing on award-level data rather than agency, recipient, or state aggregates (e.g., usa_spending_by_agency, usa_spending_by_recipient).

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 through its list of filterable fields (keyword, agency, recipient, etc.), suggesting when to use it for award searches. However, it lacks explicit guidance on when to choose this tool over sibling alternatives like usa_spending_by_agency or usa_spending_by_recipient, and does not mention any prerequisites or exclusions.

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