Open-Meteo MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the source models (AROME, ARPEGE) and their geographic focus, which adds some context. However, it doesn't describe critical behaviors like rate limits, authentication needs, 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. It wastes no words and directly states what the tool does, including key details about models. Every part of the sentence earns its place by adding value (e.g., specifying the French source and model names).

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 behavioral details (e.g., rate limits, auth), usage guidance versus siblings, and any explanation of return values or errors. While concise, it doesn't provide enough context for an agent to confidently use this tool without relying heavily on the schema alone.

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 documented in the schema itself. The description adds no specific parameter information beyond what's in the schema (e.g., it doesn't explain how 'hourly' or 'daily' arrays interact, or clarify model-specific constraints). With high schema coverage, the baseline is 3, as the description doesn't compensate with additional param semantics.

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 French Météo-France models including AROME (high-resolution France) and ARPEGE (Europe).' It specifies the action ('Get weather forecast'), the source ('French Météo-France models'), and mentions specific models (AROME, ARPEGE). However, it doesn't explicitly differentiate from sibling tools like 'weather_forecast' or 'ecmwf_forecast', which likely provide similar weather data from different 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?

The description provides no guidance on when to use this tool versus alternatives. It mentions the models (AROME for France, ARPEGE for Europe), which implies geographic scope, but doesn't explicitly state when to choose this over sibling tools like 'weather_forecast' or 'ecmwf_forecast'. No exclusions, prerequisites, or comparative advice are given.

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