get_air_quality

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

With no annotations, the description must fully disclose behavioral traits. It explains that days=1 returns current values and days>1 returns daily average forecasts, which is key behavior. However, it does not mention data source, update frequency, coordinate validation, or potential errors. The disclosure is adequate but not comprehensive.

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 long, with the first sentence stating the primary function and the second explaining the effect of the 'days' parameter. Every sentence is essential and adds value. It is front-loaded and avoids unnecessary words.

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?

Given that an output schema exists (reducing the need to explain return values), the description covers the core functionality well. It explains the difference between current and forecast data. However, it could be more complete by mentioning any limitations (e.g., geographic coverage) or how it compares to the sibling 'get_weather'. Overall, fairly complete for a tool with three parameters.

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 input schema already provides full descriptions for all three parameters (100% coverage). The description repeats the distinction for the 'days' parameter (1 vs. >1) that is already in the schema. Thus, the description adds minimal semantic value beyond what the schema provides, earning a baseline score of 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?

The description clearly states the tool returns PM10 and PM2.5 air quality data based on latitude and longitude. It specifies the resource (air quality) and the verb (returns), making the purpose clear. However, it does not explicitly differentiate from the sibling tool 'get_weather', which might have overlapping functionality.

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 explains the behavior for different 'days' values (current vs. forecast), which provides implicit usage context. However, it does not offer explicit guidance on when to use this tool instead of alternatives like 'get_weather', nor does it mention any prerequisites or conditions.

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