Predicción horaria

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

No annotations are provided, so the description carries the burden. It discloses the delivered information (temperature, sky, precipitation, wind per hour) and the temporal scope (current and following days), but does not mention potential errors, data source, or limitations (e.g., limited to Spain, max 2 days). It is neither misleading nor overly opaque, but lacks deeper behavioral detail.

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, concise phrase that front-loads the core purpose ('Predicción meteorológica hora a hora') and includes the key variables. Every word adds value, and there is no redundancy or fluff.

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 simple tool with 2 parameters and no output schema, the description covers the essential information: what it does, the geographical scope (Spanish municipality), and the forecast variables. It could be enhanced with a brief note on how it differs from 'prediccion_diaria' or that it covers up to 2 days (though that is in the schema). Overall, it is sufficiently complete for an agent to select and invoke the tool correctly.

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 provides descriptions for both parameters ('municipio' and 'dias') with 100% coverage. The tool description adds no extra parameter semantics beyond what the schema already offers. Since coverage is high, the baseline score of 3 is appropriate; the description does not compensate or add value.

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 it provides hourly (hora a hora) meteorological forecasts for a Spanish municipality, listing the specific variables (temperature, sky, precipitation, wind). This distinguishes it from sibling tools like 'prediccion_diaria', which would be daily, and 'observacion_estacion', which is observational. The resource and granularity are explicit.

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 implies usage for hourly forecasts, but does not explicitly state when to use it over siblings such as 'prediccion_diaria' or 'observacion_estacion'. It provides no exclusions or alternative recommendations. The schema does hint at using 'buscar_municipio' for ambiguous municipality names, but this is not in the tool description itself.

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