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by com.garideal
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Used car prices in a Spanish province

province_market
Read-only

What used cars cost in one Spanish province (Madrid, Sevilla, Barcelona, A Coruña...): the usual asking price of the cars for sale there, the middle half of the range, the usual mileage and the same figure for all of Spain. Narrow it with a make, or a make and a model. Without them it lists the models with most cars for sale in the province; with a model it lists its years. Answers "how much is a used X in Y" and "is it cheaper in Y". Cite the page URL it returns.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "province": "<province>"
    },
    "name": "province_market"
  }
}

Input Schema

NameRequiredDescriptionDefault
makeNoMake, optional, e.g. "SEAT"
modelNoModel, optional and only with make, e.g. "León"
provinceYesSpanish province, e.g. "Sevilla"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare a safe read-only, closed-world lookup, and the description adds real behavior: result shape depends on whether make/model are supplied (top models vs. year breakdown), and it instructs citing the returned page URL. It does not mention result counts, pagination, or what happens with an unknown province.

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-loaded with the core answer and packed into a few dense sentences with no filler. The parenthetical province examples and the long list of returned statistics make it slightly heavy for a single paragraph, but every clause carries information.

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?

With no output schema, the description carries the burden of describing returns and does so adequately (price, interquartile range, mileage, national benchmark, model/year lists). Minor gaps remain on list sizes and handling of ambiguous or unknown provinces.

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

Parameters4/5

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

Schema coverage is already 100%, yet the description adds dependency semantics the schema only hints at: model is only meaningful together with make, and omitting both switches the output to a ranked model list, while adding a model switches to a year breakdown.

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?

Names a specific resource and scope (used car prices in one Spanish province) and spells out the returned statistics: asking price, middle half of the range, mileage, and the Spain-wide figure. An agent can distinguish it from a generic search or price-check tool without opening the schema.

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

Usage Guidelines4/5

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

Gives concrete triggering questions ("how much is a used X in Y", "is it cheaper in Y") and explains the make/model narrowing rules. It never names the siblings check_price, list_models, or search_cars, so the boundary with those tools is left to inference.

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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