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cyntrica

Gov Data MCP

by cyntrica

epa_aqs_monitors

Read-only

Find EPA air quality monitoring stations by pollutant, location, and date. Returns station details, measurement types, and operating agencies.

Instructions

Find air quality monitoring stations from EPA AQS. Returns monitor locations, operational dates, measurement types, and operating agencies. Parameters: '14129' (Lead (Pb)), '42101' (CO (Carbon Monoxide)), '42401' (SO2 (Sulfur Dioxide)), '42602' (NO2 (Nitrogen Dioxide)), '44201' (Ozone), '81102' (PM10), '88101' (PM2.5 (FRM/FEM)), '88502' (PM2.5 (non-FRM, e.g. continuous)). Useful for finding what is being measured and where. Requires AQS_API_KEY and AQS_EMAIL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bdateYesBegin date YYYYMMDD
edateYesEnd date YYYYMMDD
paramYesAQS parameter code: '14129' (Lead (Pb)), '42101' (CO (Carbon Monoxide)), '42401' (SO2 (Sulfur Dioxide)), '42602' (NO2 (Nitrogen Dioxide)), '44201' (Ozone), '81102' (PM10), '88101' (PM2.5 (FRM/FEM)), '88502' (PM2.5 (non-FRM, e.g. continuous))
stateYes2-digit state FIPS code: '06' (CA), '48' (TX)
countyNo3-digit county FIPS code
Behavior4/5

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

Annotations declare readOnlyHint=true, which the description aligns with. The description adds behavioral context beyond annotations by disclosing that it 'Requires AQS_API_KEY and AQS_EMAIL' and describing the return fields (monitor locations, operational dates, measurement types, operating agencies). No contradictions found.

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

Conciseness4/5

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

The description is reasonably concise and front-loaded with the primary purpose. It follows a logical structure: purpose, returns, parameters, use case, requirements. The parameter listing is lengthy but serves as a quick reference. No unnecessary fluff.

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

Completeness4/5

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

With no output schema, the description compensates by listing return fields and authentication requirements. It covers the essential inputs and outputs for a monitoring-station lookup tool. It does not mention pagination or date-range limitations, but given the tool's moderate complexity, it is fairly complete.

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 already documents all parameters. The description repeats the parameter codes and meanings, adding marginal value. However, it does mention external requirements (AQS_API_KEY, AQS_EMAIL) not in the schema, which is useful, but the core parameter explanations are redundant.

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 opens with a specific verb+resource: 'Find air quality monitoring stations from EPA AQS.' It further specifies what is returned (locations, dates, measurement types, operating agencies), clearly distinguishing it from sibling EPA tools like epa_aqs_daily or epa_air_quality.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Useful for finding what is being measured and where' implies usage context but does not explicitly differentiate from alternatives or state when not to use this tool. Unlike the TDQS example, it names no sibling alternatives and provides no exclusion criteria.

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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