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

With no annotations the description carries the full burden and largely meets it: it discloses the upstream source, that no API key is needed, a 30-minute cache (staleness), and a per-call x402 price of $0.02 USDC on a named chain. It stops short of describing error behavior or response shape, but the operational facts an agent needs are present.

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?

Purpose is front-loaded and the operational facts are useful, but the pollutant list is restated in the 'Use this when...' sentence ('US + European AQI, PM2.5 and ozone'), and a typo ('uS') plus the trailing pricing clause add noise that could be trimmed.

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?

For a no-annotation, no-output-schema tool, the description supplies source, auth, caching, cost, and the fields returned, which is close to complete. It could still clarify how city vs lat/lon resolve, but the essential calling context is covered.

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 description coverage is 100%, so the baseline is 3. 'By city or coordinates' hints at the either/or usage, but the schema already states 'Or provide lat/lon instead'; the description adds no unit, format, or disambiguation detail for the three required-but-either/or parameters.

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?

Names a specific resource (live air quality) and enumerates the exact payload: US AQI, European AQI, PM2.5, PM10, O3, NO2, SO2, CO. It also names the data source (Open-Meteo CAMS models), so an agent can distinguish it from live_weather without opening the 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 an explicit when-to-use clause ('when an agent needs US + European AQI, PM2.5 and ozone by city') and a strong rationale to prefer it over model recall. It does not, however, state when NOT to use it or contrast it against the nearest sibling (live_weather).

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