weather_forecast

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

The description is minimal, stating only the forecast period and included data types. It does not disclose behavioral traits such as data source, update frequency, or limitations. With no annotations provided, the description carries the full burden but offers only basic transparency.

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, well-structured sentence that conveys all essential information without redundancy. Every element serves a purpose.

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 the low complexity (2 simple parameters, no nested objects, no output schema), the description adequately covers the tool's purpose, inputs, and outputs. It provides sufficient context for an AI agent to understand and select the 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 coverage is 100% with 'lat' and 'lng' described as Latitude/Longitude. The description adds no extra meaning beyond 'for a coordinate', so it aligns with the baseline score for 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 clearly states it retrieves a 7-day weather forecast for a coordinate, specifying daily temperature, precipitation, wind, sunrise, and sunset. This distinguishes it from sibling tools like 'weather_current' and 'weather_historical', which address different timeframes or conditions.

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 implies usage for a 7-day forecast at a coordinate but does not explicitly state when not to use or compare with alternatives like 'weather_current' for current conditions. The context from sibling names provides cues, but the description itself lacks direct guidance.

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