get_air_quality

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

With no annotations, the description carries full burden and excels: it discloses the geographic coverage limitation, the model-forecast nature, the possibility of an empty response due to stale/incomplete runs, and that an out-of-coverage notice differs from a blank response. This goes well beyond basic behavior.

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 dense but well-structured: a one-line summary, followed by output specifics, coverage/limitations, edge-case behavior, and parameter notes. Every sentence adds relevant information without redundancy, achieving conciseness through organization rather than brevity for its own sake.

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 the tool's moderate complexity and the existence of an output schema (which covers return values), the description covers all necessary context: what it returns, geographic coverage, data source caveats, how to handle edge cases, and parameter preparation. It leaves no obvious gaps for an agent to misuse the 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?

Schema coverage is 0%, so the description must compensate. The Args section provides decimal examples for latitude/longitude (Vienna coordinates) and explicitly states 'Geocode city names to coordinates yourself,' giving meaningful semantic guidance beyond the bare number type in the schema.

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 opens with a specific verb and resource: 'Get air quality for a location: pollutants now and the AQI outlook.' It further details the exact pollutants (NO₂, O₃, PM10, PM2.5) and the European Air Quality Index bands, making it unmistakably distinct from sibling weather/storm tools.

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?

It provides clear context and restrictions: 'serves Austria and the Alpine region only,' 'model forecasts, not station measurements,' and instructs users to geocode city names themselves. However, it does not explicitly name alternatives or state when not to use this tool versus its siblings, stopping 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.