get_forecast

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

No annotations are provided, so the description must convey behavioral context. It discloses the forecast's timeframe (3 days) and geographic scope (Chinese cities), which is helpful. It does not mention output format, units, or failure behavior, but the presence of an output schema covers some of that information externally.

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 extremely concise and front-loaded: one purpose sentence and one parameter line with examples. Every element adds value, and there is no filler or redundancy.

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 simple one-parameter tool with an output schema, the description is almost complete. The main gap is the absence of differentiation from the sibling get_weather, which could cause incorrect tool selection despite the clear purpose and parameter guidance.

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 offers no description for the city parameter (0% coverage). The description compensates by explaining that city is a Chinese city name and gives concrete examples (北京, 上海, 广州), making the expected input clear and actionable.

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's function: retrieving a 3-day weather forecast for Chinese cities. It includes a specific verb (获取), resource, scope, and time window. However, it does not explicitly differentiate itself from the sibling get_weather, so an agent may not know which tool to choose for a given request.

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 when to use this tool—when a Chinese city's 3-day forecast is needed—but provides no explicit guidance on alternatives or conditions. It does not mention get_weather or explain cases where one tool should be preferred over the other.

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