Observación de estación

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

No annotations are provided, so the description carries the disclosure burden. It explains input options (station name or idema) and the default to Madrid-Retiro, which is useful. However, it does not disclose error behavior, data availability, or the response format.

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?

Two sentences that are both informative and efficiently worded; no filler words.

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 single-optional-parameter read tool, the description covers what the tool returns and how to specify input. The lack of an output schema is partly mitigated by listing the data fields returned, though error/edge-case behavior is not mentioned.

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 schema description fully covers the 'estacion' parameter (100% coverage), including examples and default. The tool description repeats the same information without adding new meaning, so baseline 3 is appropriate.

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?

States clearly that it returns the latest conventional meteorological observation from an AEMET station, listing measured variables (temperature, humidity, wind, precipitation, pressure). This distinguishes it from sibling forecast and warning tools.

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?

Provides clear context: use for the latest observation. It does not explicitly mention alternatives like prediccion_diaria or prediccion_horaria, but the distinction is evident from the description.

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