Open Meteo MCP Server

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the forecast types (hourly/daily) but doesn't cover critical aspects like rate limits, authentication needs, error conditions, response format, or data freshness. For a weather API tool with 6 parameters, this leaves significant behavioral gaps unaddressed.

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 communicates the core functionality without unnecessary words. It's appropriately sized for a straightforward weather forecast tool and front-loads the essential information. Every word earns its place in this concise formulation.

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 (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what the forecast data looks like, how results are structured, or any limitations beyond what parameters imply. For a forecast tool that likely returns complex meteorological data, more context about the response would be valuable for the 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 fully documents all 6 parameters. The description adds minimal value beyond the schema by mentioning 'hourly and daily' forecasts, which corresponds to two boolean parameters. However, it doesn't provide additional context about parameter interactions or usage patterns beyond what's already in the structured schema.

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 verb ('Get') and resource ('weather forecast') with specific scope ('hourly and daily') and target ('for a location'). It distinguishes from siblings like get_current_weather by specifying forecast data rather than current conditions, though it doesn't explicitly name alternatives. This makes the purpose clear but not fully differentiated from all siblings.

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 like get_current_weather or get_historical_weather. It doesn't mention prerequisites, timing considerations, or specific use cases. The agent must infer usage from the name and parameters alone, which is insufficient for optimal tool selection.

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