get_weather_forecast

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

No annotations are provided, so the description must disclose behavioral traits. It states the forecast covers 3-4 days but lacks details on data source, update frequency, or any limitations. The description is too minimal for full 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 extremely concise: one line in Chinese stating the purpose, followed by a clear parameter description in English. No wasted words; information is front-loaded.

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 tool's simplicity (one parameter, no output schema, no annotations), the description covers the essential aspects. It could mention that the forecast is not current weather, but overall it is adequate for the complexity level.

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 schema has 0% description coverage, but the description adds example values ('北京市', '上海市', '广州市') which clarify the expected format beyond the schema's plain 'string' type. However, it could specify required format (e.g., city name must include '市').

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 retrieves a weather forecast for a specified city, covering 3-4 days. It uses specific verb ('get') and resource ('weather forecast'), and distinguishes from siblings like 'get_current_weather' (current vs forecast) and 'search_city' (search vs forecast).

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 provides an example of city format (e.g., '北京市'), but does not explicitly state when to use this tool versus its siblings 'get_current_weather' or 'search_city'. Usage context is implied but not spelled out.

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