air-quality

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

No annotations are provided, so the description carries full burden. It discloses the data source (CAMS), update frequency (hourly), and specific data returned (AQI category, PM2.5, PM10, etc.). However, it could be more transparent about geographic scope—'US AQI' implies a US standard but the lat/lon input suggests global coverage, which might cause ambiguity.

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 two sentences with no wasted words. The first sentence defines the tool's core function, and the second lists returned data and use cases. It is front-loaded and efficient.

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?

No output schema exists, so the description must explain return values. It lists AQI category, specific pollutants (PM2.5, PM10, etc.), and UV index. It also mentions update frequency and data source. However, it omits units (e.g., µg/m³ for particulate matter) and could clarify whether the AQI uses US EPA standards exclusively. These are minor gaps for a tool with simple inputs.

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?

Both parameters (lat, lon) are fully described in the input schema with decimal degree examples. The description adds 'any lat/lon' but this does not extend the meaning beyond the schema. With 100% schema description coverage, the baseline is 3, and the description provides no additional parameter semantics.

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 it returns 'Real-time US AQI and pollutant readings for any lat/lon', specifying the verb (returns), resource (AQI and pollutants), and scope (US AQI, global lat/lon). Among sibling tools like 'weather' and 'weather-alerts', it distinguishes itself by focusing on air quality metrics and pollution data.

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 explicit use cases: 'health advisories, outdoor event planning, environment-sensitive routing, or regulatory compliance checks'. While it doesn't explicitly state when not to use or compare with alternatives like a general weather tool, the listed use cases offer clear guidance on appropriate contexts.

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