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 states the tool 'returns year-by-year data with counts and rates,' which is useful, but lacks critical behavioral details: it doesn't mention if this is a read-only operation, potential rate limits, authentication needs, data freshness, or error handling. For a data retrieval tool with no annotations, 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 front-loaded with the core purpose, followed by specific details on offense categories and return format. Every sentence earns its place: the first defines the tool, the second lists offenses, and the third specifies the output. It's efficiently structured with zero waste.

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 no annotations and no output schema, the description is moderately complete: it covers purpose, offense details, and return format. However, it lacks behavioral context (e.g., safety, limits) and doesn't fully explain parameter interactions (e.g., how state and ori affect results). For a 5-parameter tool with no structured safety info, it should do more to compensate.

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 parameters. The description adds value by explaining the offense codes in detail (e.g., 'V (violent crime)', 'P (property crime)'), which clarifies semantics beyond the enum in the schema. However, it doesn't add context for other parameters like state or ori beyond what the schema provides.

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 summarized UCR crime data from the FBI at national, state, or agency level.' It specifies the resource (UCR crime data), the source (FBI), and the granularity levels (national, state, agency). It distinguishes itself from sibling tools by focusing on FBI crime data, unlike BEA, BLS, CDC, etc., tools listed.

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 by specifying the levels (national, state, agency) and offense categories, but does not explicitly state when to use this tool versus alternatives. It mentions no prerequisites, exclusions, or direct comparisons to other crime-related tools (e.g., fbi_arrest_data, fbi_expanded_homicide), leaving the agent to infer context.

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