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Sequía agrícola (Copernicus)

sequia_agricola
Read-onlyIdempotent

Qué parte de España, de una comunidad autónoma o de una provincia está en sequía según el Indicador Combinado de Sequía (CDI) del Observatorio Europeo de la Sequía (Copernicus): % del territorio en vigilancia (falta lluvia), aviso (también falta humedad en el suelo), alerta (además la vegetación lo acusa) o recuperación. Un dato cada diez días, con 3 a 5 semanas de retraso. Sin lugar, España y las provincias más afectadas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lugarNoProvincia o comunidad: 'Jaén', 'Cataluña', 'Comunidad de Madrid'. Vacío o 'España' para el total.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds genuinely useful behavior: a ten-day measurement cadence with 3-5 weeks of lag, and the four CDI severity categories — latency is exactly the kind of context an agent needs to interpret freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads what is measured and by whom, then the categories, then cadence and the default behavior. Dense but every clause carries information; the only slightly redundant piece is repeating the empty/'España' behavior already in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read-only tool with no output schema, the description supplies the domain, the indicator categories and the data latency, which is enough to call and interpret it correctly. It stops just short of describing the actual return shape (e.g. percentages per category per region).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single `lugar` parameter is fully documented in the schema. The description only restates the empty/'España' default and adds that omitting it also returns the most affected provinces — marginal value beyond the schema, so baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (drought status by region per Copernicus CDI) and the exact scope of the answer (% of territory in vigilancia/aviso/alerta/recuperación). This is clearly distinguishable from the reservoir and river-flow siblings without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: the description explains the default behavior when `lugar` is omitted, which hints at how to call it, but never says when to prefer this over the embalse/caudal siblings or what conditions make it inappropriate.

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

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