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 describes the data format and scope (e.g., NIBRS offense codes, detailed fields), but does not disclose critical behavioral traits such as data availability constraints, rate limits, authentication requirements, error handling, or response format. For a data retrieval tool with no annotations, this leaves significant gaps in understanding how the tool behaves in practice.

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, starting with the core purpose and immediately elaborating on key details. Every sentence adds value: the first states the purpose, the second explains the data's detailed nature, and the third provides concrete offense code examples. There is no wasted text, and the structure efficiently conveys essential information.

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 complexity of crime data retrieval with 6 parameters and no output schema, the description is moderately complete. It covers the purpose, data scope, and offense codes, but lacks details on behavioral aspects (e.g., rate limits, error handling) and output format. With no annotations and no output schema, the description should provide more context on how results are returned and any usage constraints to be fully adequate.

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 thoroughly. The description adds minimal parameter semantics by providing examples of NIBRS offense codes (e.g., '13A' for aggravated assault) and noting the tool's focus on detailed data, but does not significantly enhance understanding beyond what the schema provides. This meets the baseline for high schema coverage.

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 NIBRS (National Incident-Based Reporting System) data from the FBI.' It specifies the verb ('Get'), resource ('NIBRS data'), and distinguishes it from summarized UCR data by detailing included elements like victim/offender demographics, relationships, weapons, location, and time of day for 71 offense types. This differentiation from potential alternatives (like UCR data) is explicit and comprehensive.

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: for detailed incident-based crime data rather than summarized UCR data. It implicitly suggests alternatives by contrasting with 'summarized UCR data,' but does not explicitly name sibling tools or specify when not to use it. The guidance is useful but lacks explicit exclusion criteria or named alternatives.

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