US Government Open Data MCP

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: authentication requirements ('Requires AQS_API_KEY and AQS_EMAIL'), data source ('EPA's Air Quality System'), signup information, and format constraints ('YYYYMMDD format'). It doesn't mention rate limits, pagination, or error handling, but covers essential operational context beyond basic functionality.

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 efficiently structured with purpose first, followed by parameter details, service options, state codes, constraints, and authentication requirements. Each sentence serves a clear purpose, though the parameter listing is somewhat dense. It could be slightly more front-loaded by moving authentication requirements earlier, but overall it's well-organized with minimal 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?

For a tool with 6 parameters, no annotations, and no output schema, the description provides substantial context: purpose, parameter semantics, service options, format constraints, authentication requirements, and even signup information. The main gap is lack of output format description, but given the tool's complexity and absence of structured metadata, the description does a commendable job of making the tool usable.

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%, providing detailed parameter documentation. The description adds value by explaining parameter code meanings (e.g., '14129' = 'Lead (Pb)'), listing all service options with explanations, and providing state code examples. However, it doesn't add significant semantic context beyond what's already well-documented in the schema descriptions, meeting 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 explicitly states the tool's purpose: 'Get air quality data from EPA's Air Quality System (AQS).' It specifies the data type ('annual summary data by state'), granularity ('county-level monitor readings'), and scope ('criteria pollutants'), making the verb+resource combination highly specific. It clearly distinguishes this tool from its sibling 'epa_aqs_daily' by mentioning multiple service types including 'dailyData', implying this tool is more 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 the tool by listing available parameters, services, and state codes, and specifying date constraints ('bdate/edate must be in same year'). However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among the many sibling tools, though it implies differentiation from 'epa_aqs_daily' by including it as a service option.

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