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

No annotations are provided, so the description must disclose behavioral traits. It mentions the data source (OpenAQ) and pollutants, but does not disclose details such as whether data is real-time or historical, what the return format is, any API key requirements, or error behavior. This is a significant gap for a tool with no annotation coverage.

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 a single, focused sentence that front-loads the core purpose and key details. No fluff or redundancy.

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 output schema and no annotations, the description should explain return values and behavioral details. It only states the data categories and scope, leaving the agent without information on output structure, required parameters (location is optional), or potential failure modes. This is incomplete for a simple tool.

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?

The schema fully covers the only parameter 'location' with examples, achieving 100% schema description coverage. The description adds context about pollutants but does not add meaning beyond the schema. Baseline 3 is appropriate.

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 tool's purpose: 'Get air quality data (OpenAQ) — PM2.5, PM10, O3, NO2 for a city.' It identifies a specific verb, resource, and the data scope (pollutants and city). This distinguishes it from sibling tools, none of which relate to air quality.

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 contexts for air quality data retrieval. It clearly specifies the scope (city and pollutants), making it obvious when to use the tool. However, it does not explicitly exclude alternatives or mention when-not-to-use scenarios, so it falls short of a 5.

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