US Government Open Data MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations provide readOnlyHint=true, which the description doesn't contradict. The description adds valuable behavioral context beyond annotations: it specifies the data source (CDC PLACES), the population threshold (> 50,000), and the output format (each row contains ALL measures as separate columns). This gives the agent important context about what to expect from this tool.

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 perfectly concise and well-structured. Two sentences efficiently convey: 1) what the tool does and its scope, and 2) the output format. Every word earns its place with no redundancy or unnecessary 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 that annotations cover the read-only nature and the schema fully documents parameters, the description provides excellent context about the tool's purpose, scope, and output format. The main gap is the lack of output schema, but the description compensates by explaining the return format (rows with all measures as separate columns). For a data retrieval tool with good annotations and schema coverage, this is quite complete.

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?

With 100% schema description coverage, the input schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions city-level data and population thresholds, which relate to the 'city' and 'state' parameters indirectly, but doesn't provide additional semantic context about parameter usage.

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 city-level health indicators from CDC PLACES' with specific examples of indicators (obesity, diabetes, smoking, etc.) and scope (every U.S. city with population > 50,000). It distinguishes itself from sibling tools like 'cdc_places_health' by focusing specifically on city-level data with all measures in a single row.

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 when to use this tool: for obtaining comprehensive health indicators at the city level for U.S. cities with population over 50,000. It doesn't explicitly mention when NOT to use it or name specific alternatives, but the specificity of scope (city-level, all measures in one row) provides good implicit guidance.

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