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

With no annotations, the description carries the full burden and does well: it discloses pricing, a free-call allowance, the data provenance (Copernicus CAMS via Open-Meteo), and that responses carry a signed receipt. It omits precedence rules when both city and coordinates are supplied, and says nothing about failure or rate-limit 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?

Three tight sentences, front-loaded with what the tool returns before moving to inputs, pricing, and the free tier. No filler, and every clause carries information an agent needs to decide and invoke.

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 output schema and no annotations, the description does the work of naming the returned quantities and the billing model, which is enough to call correctly. It leaves a small gap around precedence for the city-vs-coordinates choice and error/limit behavior.

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 100%, so the baseline is 3, but the description adds real meaning the schema does not express: the parameters are an either/or choice, since all three are optional and no oneOf/required constraint is encoded. It does not, however, resolve precedence if both are passed.

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 verb+resource ('Current air quality at a place') and enumerates the concrete outputs (PM2.5, PM10, US and European AQI) plus the upstream source. It implicitly separates itself from weather_now by naming air-quality-specific metrics, but never explicitly distinguishes itself from that sibling.

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 clear invocation context: supply coordinates or a city name, and discloses the cost model ($0.001 per call, first 3 priced calls free). It does not state when to prefer one input form over the other or name alternatives, so it stops short of full when/when-not guidance.

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