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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: data sources (Open-Meteo / NWS), cost per call, the HTTP method (GET), and the specific output categories. No contradiction with 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?

The description is a single compact sentence that front-loads the core purpose, then lists the key outputs and practical metadata (source, cost, endpoint). Every clause contributes useful information with no filler.

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?

There is no output schema, so the description helps by naming what the caller receives: current conditions, hourly rain probability, multi-day forecast, and a plain answer. It also includes source and cost. Some minor details like response format or units are absent, but for this simple read-only weather tool the description is nearly complete.

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 covers all parameters (q, lat, lon, days) with 100% description coverage, so the schema does the heavy lifting. The description adds no additional parameter-level meaning beyond saying the forecast is multi-day, which is acceptable given the high schema coverage.

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 specifies a concrete resource ('Weather forecast') and enumerates distinct output types: current conditions, 12-hour rain probability, multi-day forecast, and a direct rain answer. This clearly separates it from weather-related siblings like v1_weather_alerts, v1_sun, and v1_air_quality.

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 communicates clear use cases: general weather forecasting, rain probability, and a simple 'will it rain' query. It does not explicitly name alternative tools or state when not to use it, but the strong purpose framing makes the intended usage obvious.

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