get_weatherCurrent weather and short forecast for a city or coordinates. Works for Chinese cities too.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | Latitude (alternative to city). | |
| lon | No | Longitude (alternative to city). | |
| city | No | City name, e.g. "Shanghai" / "上海". Or pass lat/lon. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / properties / city / descriptionPrevious value: -"City name, e.g. 北京 or Paris"New value: +"City name, e.g. \"Shanghai\" / \"上海\". Or pass lat/lon."Input schema / properties / latAdded value: +{
+ "description": "Latitude (alternative to city).",
+ "type": "number"
+}Input schema / properties / latitudeRemoved value: -{
- "type": "number"
-}Input schema / properties / lonAdded value: +{
+ "description": "Longitude (alternative to city).",
+ "type": "number"
+}Input schema / properties / longitudeRemoved value: -{
- "type": "number"
-}Input schema / requiredAdded value: +[]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose read-only and idempotent behavior, so the description does not need to repeat that. It adds valuable behavioral context beyond annotations: it states the output includes a 'short forecast' and that Chinese city names (including Chinese characters) are supported. This is more than the schema provides and helps the agent set expectations.
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 sentence that immediately conveys the primary function, input options, and a special capability. Every word earns its place, with no filler or repetition. Structure is optimal for quick agent comprehension.
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 read-only weather tool with 3 parameters, full schema coverage, annotations, and an output schema, the description is complete. It covers the core purpose, input modes, and a key localization feature. No additional behavior needs to be disclosed; any output details are handled by the output schema.
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 detailed descriptions for each parameter (lat, lon, city), including an example with Chinese characters. The description adds only slight reinforcement by saying 'for a city or coordinates', but this is already evident from the schema. With high schema coverage, a baseline of 3 is appropriate; no additional parameter semantics are needed.
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 with a specific verb and resource: returns current weather and a short forecast. It distinguishes from sibling tools (which focus on other domains like security, finance, domain info) by specifying weather for a city or coordinates. The added note about Chinese cities further clarifies scope.
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 gives clear context by specifying input options ('for a city or coordinates'), so an agent knows when to invoke it. It does not explicitly mention when not to use it or alternatives, but sibling tools are distinct enough that the purpose itself implies usage. No exclusions are stated, which is acceptable for a simple weather tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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