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 getting 'data and forecasts,' implying a read-only operation, but doesn't specify whether this requires authentication, rate limits, data freshness, or error handling. 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 a single, efficient sentence: 'Get air quality data and forecasts for a location.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence earns its place by specifying what is retrieved and for what scope.

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 moderate complexity (4 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what 'air quality data' includes (e.g., AQI, pollutants), how forecasts are structured, or the response format. Without annotations or an output schema, the agent lacks critical context for effective use.

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 input schema has 100% description coverage, clearly documenting all parameters (latitude, longitude, days, current) with types, ranges, and defaults. The description adds no additional parameter semantics beyond what the schema provides, such as explaining the format of returned data or interactions between parameters. Baseline 3 is appropriate since 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 air quality data and forecasts for a location.' It specifies the verb ('Get'), resource ('air quality data and forecasts'), and scope ('for a location'), which distinguishes it from siblings like get_current_weather or get_weather_forecast. However, it doesn't explicitly differentiate from get_climate_data, which might overlap in some contexts.

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 doesn't mention when-not scenarios, prerequisites, or comparisons to sibling tools like get_climate_data or get_weather_forecast. This leaves the agent to infer usage based on the tool name alone, which is insufficient for optimal selection.

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