EPA Air Quality System (AQS) MCP Server

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

With no annotations provided, the description carries the full burden. It discloses authentication behavior (email/API key usage with environment variable fallback) and date constraints (same calendar year), which are useful beyond the schema. However, it lacks details on rate limits, error handling, or response format, leaving behavioral gaps for a tool with 6 parameters.

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 well-structured with a clear purpose statement followed by parameter details and a note on authentication. It avoids redundancy and is appropriately sized, though the parameter examples list could be slightly condensed. Every sentence adds value, and it is front-loaded with the core functionality.

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, no output schema, and 6 parameters, the description is moderately complete. It covers authentication, parameter semantics, and constraints, but lacks output details (e.g., response structure) and does not fully address behavioral aspects like error cases. For a data retrieval tool with multiple parameters, more context would be beneficial.

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 baseline is 3. The description adds significant value by providing common parameter code examples (e.g., 44201 for Ozone) and clarifying date format requirements (YYYYMMDD, same calendar year), which enhances understanding beyond the schema's basic descriptions. It does not fully explain all parameters but compensates well for key ones.

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 specific action ('Get all air quality monitors') and resource ('in a state'), distinguishing it from sibling tools like 'aqs_monitors_by_box' or 'aqs_monitors_by_cbsa'. It also specifies the return content ('detailed information about monitors including location, operational dates, and measurement parameters'), making the purpose explicit and distinct.

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 implies usage through the tool name and parameter context (e.g., state-based filtering), but does not explicitly state when to use this tool versus alternatives like 'aqs_monitors_by_county' or 'aqs_monitors_by_site'. No exclusions or prerequisites are mentioned beyond parameter constraints, leaving usage context partially inferred.

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