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Autodev Listings

autodev_listings
Read-onlyIdempotent

Find used cars for sale matching criteria (make/model/price/location) — active listings from US physical & online dealers. Example: autodev_listings({ make: "Toyota", model: "Camry", year_min: 2020, price_max: 30000, zip: "94103", limit: 20, _apiKey: "your-key" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNoZIP code to center the search on (optional)
makeNoVehicle make, e.g. "Toyota" (optional)
limitNoMax listings to return (default 20, max 50)
modelNoVehicle model, e.g. "Camry" (optional)
radiusNoSearch radius in miles from zip (optional)
_apiKeyYesAuto.dev API key (1,000 free calls/mo at auto.dev)
year_maxNoNewest model year to include (optional)
year_minNoOldest model year to include (optional)
price_maxNoMaximum listing price in USD (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful context by noting listings are 'active' and sourced from 'US physical & online dealers,' but it does not disclose response format, pagination, or failure behavior.

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 compact, front-loaded with the core purpose, and includes a concrete invocation example. Every part adds value, and there is no redundant filler.

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 all parameters documented in the schema and annotations covering safety behavior, the description provides enough context for selecting and invoking the tool. The only notable absence is a description of the return shape, but no output schema exists and this is not critical for basic invocation.

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 description coverage is 100%, so the schema fully documents all nine parameters. The description's example reinforces how to pass parameters but does not add meaning beyond the schema, keeping this at the baseline.

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 opens with a specific verb and resource: 'Find used cars for sale matching criteria' and adds scope: 'active listings from US physical & online dealers.' This clearly separates it from sibling tools like autodev_valuation and autodev_vin_decode, which serve different purposes.

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?

The description makes the use case clear: retrieve used-car listings filtered by make, model, price, and location. It does not explicitly name alternatives or exclusions, but the stated purpose is distinct enough that an agent can infer when to invoke this tool versus the autodev-related siblings.

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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