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

Annotations already indicate read-only, non-destructive, idempotent behavior, so the bar is lower. The description is consistent with these annotations and adds no extra behavioral details like rate limits or error handling. It does not contradict the annotations, but also doesn't go beyond them significantly.

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 two sentences: the first states exactly what the tool returns, and the second gives usage guidance and a parameter note. It is economical, front-loaded, and every sentence earns its place. No fluff or redundancy.

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 simple tool with a single parameter and no output schema, the description covers the key aspects: what data is returned, the granularity, and example use cases. It doesn't mention error conditions or output format, but these are not critical for such a straightforward read-only tool. Overall, it provides sufficient context for an agent to decide when and how to call it.

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 schema already provides a full description of the 'city' parameter, including the note about English or Chinese names and examples. The tool description repeats this information and adds context about the intended use, but does not introduce new parameter semantics. Since schema coverage is 100%, the baseline is 3.

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?

Clearly states it returns individual monitoring-station readings within a city, including AQI, pollutant concentrations, quality rating, station name, and coordinates. The examples ('which part of Shanghai has the worst air right now') make the purpose concrete. It is easily distinguished from sibling tools like china_air_quality (city-level overview) and china_air_quality_ranking (ranking).

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?

Provides explicit guidance on when to use it: 'Use this for neighborhood-level detail within a city'. The examples illustrate ideal scenarios. It does not explicitly name alternatives, but the sibling tool list and the contrast with city-level detail make the intended use clear enough.

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