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

Beyond the readOnlyHint annotation, the description discloses the update cadence ('Updates: hourly'), data source openness ('keyless'), and the output structure (worst-first per-metro table, pollutant drivers). It gives the agent a complete behavioral picture without contradicting annotations.

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: first defines the output, second gives usage triggers, third states update frequency. No fluff, every sentence adds value, and key information is front-loaded.

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 read-only data retrieval tool with one optional parameter, the description covers the score range, geographic scope, data source, output components, update frequency, and appropriate invocation scenarios. The schema handles the parameter details, so nothing essential is missing.

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 only parameter, 'days', is fully described in the schema (range, behavior, Gold tier requirement). The tool description adds no extra parameter semantics, but since schema coverage is 100%, the baseline of 3 is appropriate.

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 starts with a specific verb 'Returns' and a precise resource: a 0-100 US air-quality burden score with detailed output fields (worst_metro, share_unhealthy, dominant_pollutant) and a per-metro table. It clearly distinguishes itself from generic air-quality tools by specifying the 12-major-metro scope and the keyless Open-Meteo/CAMS data source.

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 description explicitly states when to call it: 'when the user asks about current air quality, wildfire smoke, ozone, or which US city is worst right now' and lists operational contexts like outdoor logistics and respiratory staffing. It does not name alternatives or provide exclusion criteria, but the use cases are clear and practical.

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