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Gasóleo agrícola hoy

gasoleo_hoy
Read-onlyIdempotent

Precio medio del gasóleo B (agrícola) en las gasolineras, último día publicado: media de España, de la Comunitat Valenciana y de la provincia que se pida, con su puesto entre las provincias peninsulares y Baleares y las más baratas y caras del día. Precio con impuestos, venta al público.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
provinciaNoOpcional: provincia (p. ej. Zaragoza, Teruel, Valencia).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds real behavioral content beyond them: the data is the last published day, prices include taxes, and it is a retail public-sale price, plus the returned comparison metrics. That extra context is genuinely useful.

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?

A single dense sentence, front-loaded with the resource and price type before the scope details. It earns its length because there is no output schema to describe the returns, but the long clause chain sacrifices some readability.

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 one-optional-parameter read tool with no output schema, the description does the necessary work: it explains what is averaged, what comparisons are returned, the day basis and that taxes are included. Only the absence of guidance on default behavior when 'provincia' is omitted is a minor gap.

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 'provincia' parameter is fully documented in the schema with examples. The description only echoes it as optional ('la provincia que se pida') without adding format or default-value semantics, so baseline 3 applies.

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

Purpose4/5

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

It states a precise resource ('precio medio del gasóleo B (agrícola) en las gasolineras') and the scope of the result (Spain, Comunitat Valenciana, requested province, plus ranking and extremes). This clearly identifies the retrieved data. However, it never distinguishes itself from siblings like precio_ultimo or historico, so the agent must infer the boundary.

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 only implied: the mention of the 'último día publicado' signals a latest-snapshot query, but there is no explicit when-to-use, when-not-to-use, or routing toward alternates such as precio_ultimo or historico. The agent can guess, but nothing is stated.

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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