Mountain bulletin for a Spanish mountain area

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 does this well by stating the data source (AEMET), the year-round nature, the mountain-range scope, the content of the bulletin (forecaster prose, freezing levels, wind, thermal sensation), and the differences between forecast and past modes. The only minor gap is that it doesn't describe the exact response structure or error behavior, but for a read-only retrieval tool this is a limited shortfall.

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 well structured: purpose and content are front-loaded, followed by mode behavior, then usage guidance pointing to a sibling. Every sentence earns its place and there is no filler or redundant repetition of the input schema.

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?

For a tool with only three simple parameters, no output schema, and no annotations, the description is remarkably complete. It tells the agent what the tool returns, for which areas, with which modes, and how it relates to the sibling get_forecast. An agent has everything needed to decide when to invoke it and what to expect.

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 baseline is 3. The description adds some contextual flavor—such as the bulletin being written for mountaineers and skiers and covering the mountain range as a whole—but it largely restates what the schema already documents for area, day, and mode.

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 opens with a specific verb and resource: 'Returns the AEMET mountain bulletin for one of Spain's nine mountain areas...' and even names the areas, which makes the tool's scope unmistakable. It also points to the sibling get_forecast as the tool to avoid for mountain use, which distinguishes it from the general forecast tool.

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?

It explicitly tells the agent when to use this tool: 'use them instead of get_forecast for anything above the valley floor.' It also differentiates between mode='forecast' and mode='past', clarifying that forecast covers today to day 3 and past summarizes the last 24 hours, so the agent can choose the correct mode without extra inference.

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