Air quality at a Philippine location

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by specifying the data source (Open-Meteo, no API key), the exact pollutants and AQI categories returned, and the ~80 city coverage limitation. It does not mention error handling or rate limits, but the added context suffices.

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 sentences, front-loaded with the core function, then return details and limitations. No redundant or filler content.

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?

With output schema present and rich annotations (read-only, idempotent), the description sufficiently covers data source, return items, and scope. Limitation about unlisted locations is also disclosed. No major gaps for a single-parameter lookup tool.

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 covers the single parameter (location) with examples, so baseline is 3. The description reinforces that location must be a Philippine city and adds coverage limitations, but does not fundamentally extend the parameter's semantic meaning.

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 real-time air quality for a Philippine city, listing specific pollutants and AQI metrics. It distinguishes itself from weather-related siblings by focusing on air quality data.

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?

It provides clear context: use for Philippine city air quality, covers ~80 major cities, and notes a limitation for unlisted locations (future coordinate support). It does not explicitly name alternative tools for other data types, but the purpose is unambiguous.

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