get_air

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

No annotations exist, so the description carries the full burden. It does disclose the conceptual payload (both AQI standards, particulate load, forecast window), which is real behavioral value, but says nothing about data freshness, source, whether an API key is needed, or how invalid coordinates or out-of-range horizons are handled.

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?

Two sentences: the first front-loads what the tool returns, the second gives the decision context. Nothing is repeated and nothing is wasted.

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?

With no annotations and no output schema, the description does the heavy lifting well by enumerating the returned data and the use case. It falls short of full completeness only on operational details — provenance/freshness of readings and error behavior — which matter for a data-fetch 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 only 33% — only 'hours' is documented (default 12, max 48). The description compensates by framing input as 'a coordinate' and output as a 'forecast window', which maps lat/lon and the horizon semantics, though it adds no tolerance, format, or range detail for the coordinates themselves.

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?

States a specific resource (air quality at a coordinate) and enumerates the returned data: European and US AQI bands, particulate load, and forecast window. That scope cleanly separates it from get_weather, get_terrain, and get_daylight without the agent needing to open any schema.

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?

Gives two concrete, actionable when-to-use triggers: before prolonged outdoor exertion, and before recommending a walking route to someone with respiratory sensitivities. It omits explicit when-not conditions and never names an alternative sibling for overlapping queries (e.g. general weather), which keeps it below a 5.

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