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 discloses that the tool requires 'AQS_API_KEY and AQS_EMAIL' for authentication, which is useful behavioral context. However, it does not mention other traits like rate limits, error handling, or data format details, leaving gaps in transparency for a tool with no annotations.

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 key details like parameters, usage context, and requirements in four concise sentences. Every sentence adds value without redundancy, making it efficient and well-structured.

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 does well by covering purpose, parameters, usage context, and authentication requirements. However, it lacks details on output format (e.g., structure of returned data) and potential limitations, which would enhance completeness for a tool with 5 parameters and no structured output info.

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 lists parameter codes for 'param' but does not add meaning beyond what the schema provides for other parameters like 'state', 'bdate', 'edate', or 'county'. Baseline 3 is appropriate as 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 verb ('Get') and resource ('daily air quality summary data from EPA AQS'), specifying it returns daily mean, max, and observation count per monitor. It distinguishes itself from sibling tools by focusing on EPA AQS data, unlike other tools like 'epa_air_quality' or 'epa_aqs_monitors' which likely serve different purposes.

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: 'Useful for tracking day-to-day pollution levels' and suggests cross-referencing with CDC health data. However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as 'epa_air_quality' for broader air quality data.

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