air_quality

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that data is sampled across major world cities and what metrics are returned, but it omits freshness, update cadence, geographic coverage limits, and data-source 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 a single compact sentence that front-loads the resource and metrics before adding interpretive context. It avoids waste, though the final proxy clause is more contextual than operational.

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?

The output schema covers return values, and the description supplies metrics and city-level sampling scope. However, with no annotations and an undocumented parameter, it leaves gaps around parameter behavior, data freshness, and spatial limitations.

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 single optional 'detail' parameter has 0% schema description coverage, and the description never mentions it or explains what values such as 'short' mean. Since schema coverage is low, the description should compensate, but it does not.

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 names a specific resource (air quality) and concrete metrics (US AQI, PM2.5, PM10), plus its spatial scope ('sampled across major world cities'). It is clearly distinguishable from environmental siblings like radiation or climate_anomalies, though it does not explicitly contrast with them.

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 phrase 'a proxy for industrial activity, smoke drift, and chemical release' implies appropriate use cases, but the description does not state when to choose this tool over siblings such as fire_perimeters, radiation, or climate_anomalies. No exclusions or prerequisites are given.

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