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 what data is included but does not disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, data freshness, pagination, or error handling. For a data retrieval tool with no annotation coverage, this is a significant gap in behavioral context.

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 a single, well-structured sentence that efficiently conveys purpose, data content, and availability levels without any wasted words. It is front-loaded with the core action and resource, making it easy to understand 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 complexity of a 5-parameter data retrieval tool with no annotations and no output schema, the description is adequate but incomplete. It covers what data is fetched and at what levels, but lacks details on return format, data structure, potential limitations, or error conditions. For a tool with rich parameter schema but no output schema, more context on expected results would be beneficial.

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 input schema has 100% description coverage, clearly documenting all 5 parameters. The description adds value by explaining the data granularity levels (national, state, agency) which helps contextualize the 'state' and 'ori' parameters, but does not provide additional syntax or format details beyond what the schema already specifies. Baseline 3 is appropriate when 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 verb 'Get' and the resource 'expanded homicide (Supplementary Homicide Report) data from the FBI', specifying it includes victim/offender demographics, weapons used, and circumstances. It distinguishes itself from sibling tools like 'fbi_crime_summarized' or 'fbi_hate_crime' by focusing specifically on detailed homicide data.

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 about data availability at national, state, or agency levels, which helps guide parameter selection. However, it does not explicitly state when to use this tool versus alternatives like 'fbi_crime_summarized' for broader crime data or 'fbi_hate_crime' for hate crime specifics, nor does it mention prerequisites or exclusions.

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