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by io.github.transparentpt
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list_makes_models

List the exact canonical car makes (brands) TransparentCars can search and price — or, given a make, that brand's models — using the exact strings the other tools expect. Call this FIRST (or whenever unsure of spelling) and pass the returned values verbatim into search_inventory / check_fair_price. No make = the list of brands; with a make = that brand's models.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_makes_models"
  }
}

Input Schema

NameRequiredDescriptionDefault
makeNoBrand to list models for, e.g. 'Renault'. Omit to get the list of brands.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the dual behavior (brands vs. models), emphasizes canonical/exact string output, and communicates that results are meant to be reused verbatim. It stops short of explicitly stating that the operation is read-only or describing the exact return format, but for a listing tool this is largely sufficient.

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

Conciseness5/5

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

The description is two sentences long, front-loaded with the core purpose, and then flows naturally into usage conditions and parameter behavior. Every sentence earns its place, with no filler or repetition of what the schema already states.

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

Completeness5/5

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

For a simple tool with one optional parameter and no output schema, the description is complete: it explains the two modes, states how results should be used, and names the consumer tools. Nothing needed to call it correctly is missing.

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 100%, so the baseline is 3. The description goes beyond the schema by clarifying that the returned values are canonical and 'exact strings' that must be passed verbatim, which reinforces why this parameter matters and how the output should be consumed. This adds meaningful context beyond the schema definition.

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?

The description clearly identifies the tool as a reference lookup for canonical car makes and models, explicitly naming the exact strings that other tools expect. It distinguishes itself from sibling tools by positioning itself as the data source to use before search_inventory or check_fair_price.

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

Usage Guidelines5/5

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

The description gives explicit, actionable guidance: call this FIRST or whenever unsure of spelling, and pass returned values verbatim into other tools. It also clarifies the two usage modes, with and without the make parameter, leaving no ambiguity about when and how to invoke it.

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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