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tyson-swetnam

EPA Air Quality System (AQS) MCP Server

aqs_list_cbsas

Retrieve Core Based Statistical Area codes for metropolitan and micropolitan regions to query EPA air quality data by geographic area.

Instructions

Get a list of Core Based Statistical Areas (CBSAs) with their codes. CBSAs are metropolitan and micropolitan statistical areas defined by the US Census. Use CBSA codes for regional air quality queries. Example: Los Angeles-Long Beach-Anaheim = "31080", New York-Newark-Jersey City = "35620".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoRegistered email address for AQS API. Optional if AQS_EMAIL env var is set.
keyNoAQS API key. Optional if AQS_API_KEY env var is set.
Behavior2/5

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 describes the tool's purpose and output format (CBSA codes with examples), but lacks critical behavioral details such as whether this is a read-only operation, if it requires authentication (though hinted in schema), rate limits, pagination, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by explanatory context and practical examples. Every sentence adds value: defines CBSAs, states usage, and provides concrete examples, with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with no output schema and no annotations, the description covers the purpose and usage well but lacks details on output format beyond examples, authentication behavior, or error cases. It's adequate but has clear gaps given the context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents the two optional parameters (email and key). The description adds no parameter-specific information beyond what's in the schema, but the baseline is 3 since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

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 ('list of Core Based Statistical Areas with their codes'), specifies what CBSAs are, and distinguishes this tool from siblings by focusing on listing CBSAs rather than performing air quality queries or listing other entities like states or counties.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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 ('Use CBSA codes for regional air quality queries') and implies it's a prerequisite for CBSA-based queries, but it doesn't explicitly state when not to use it or name specific alternatives among the sibling tools.

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

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