Open-Meteo MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves 'high-resolution data,' which adds some context about data quality, but lacks critical details such as rate limits, authentication requirements, data freshness, error handling, or response format. For a tool with 11 parameters and no output schema, 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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does, the source, and the scope, making it easy to understand at a glance. Every part of the sentence earns its place by providing essential information.

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 complexity (11 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral aspects like rate limits or errors, doesn't explain the output structure, and provides no usage guidelines. While the schema covers parameters well, the overall context for effective tool use is insufficient, especially for a data retrieval tool with many configuration options.

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%, meaning all parameters are well-documented in the input schema itself. The description doesn't add any additional meaning or context about the parameters beyond what's already in the schema (e.g., it doesn't explain how 'high-resolution' relates to parameters like 'forecast_days' or 'hourly'). Baseline score of 3 is appropriate as 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: 'Get weather forecast from Japan Meteorological Agency with high-resolution data for Japan and Asia.' It specifies the action ('Get weather forecast'), source ('Japan Meteorological Agency'), and scope ('Japan and Asia'), but doesn't explicitly differentiate from sibling tools like 'weather_forecast' or 'dwd_icon_forecast' that might provide similar functionality for other regions or sources.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'Japan and Asia' as the scope, but it doesn't clarify if this is the only tool for that region or when to choose it over other forecast tools like 'gfs_forecast' or 'ecmwf_forecast' that might also cover Asia. There's no mention of prerequisites, limitations, or specific use cases.

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