HeFeng Weather MCP Server

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states what the tool does (get weather forecast) but doesn't mention any behavioral traits like rate limits, authentication needs, error handling, or what happens with invalid inputs. For a tool with no annotation coverage, this is a significant gap in 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 appropriately concise with two sentences that directly address the tool's function and required inputs. It's front-loaded with the main purpose and wastes no words. However, it could be slightly more structured by separating usage guidance from parameter requirements.

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 no annotations and no output schema, the description is incomplete for a weather forecasting tool. It doesn't explain what the return values look like (e.g., temperature, conditions), error scenarios, or any limitations. For a tool with 2 parameters and complex forecasting options, more context is needed to be fully helpful to an AI agent.

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 description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds minimal value beyond the schema by mentioning LocationID or coordinates as input options, but doesn't provide additional semantic context. Baseline 3 is appropriate when the schema does the heavy lifting.

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 purpose: '获取指定地点的天气预报' (get weather forecast for a specified location). It specifies the verb (get) and resource (weather forecast), but doesn't differentiate from sibling tools like get_datetime or get_location_id, which are unrelated weather tools. The purpose is specific but lacks sibling distinction.

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 no guidance on when to use this tool versus alternatives. It mentions what parameters to provide (LocationID or coordinates) but doesn't indicate when this tool is appropriate compared to siblings or other weather-related tools. There's no context about use cases or exclusions.

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