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Wrench.Pro Vehicle Check

NHTSA recalls for a vehicle

get_recalls

Use when the user asks specifically about recalls or safety campaigns. Requires exact slugs from resolve_vehicle. Always tell the user to confirm against their own VIN at nhtsa.gov/recalls before acting on safety issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesMake slug from resolve_vehicle, e.g. 'ford'.
yearYes4-digit model year from resolve_vehicle.
modelYesModel slug from resolve_vehicle, e.g. 'f-150'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full disclosure burden and delivers an unusual, high-value behavioral instruction: always direct the user to verify against their own VIN at nhtsa.gov/recalls before acting. It does not disclose read-only status, data source currency, or rate limits, but the safety disclaimer is substantive context beyond any structured field.

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?

Three short sentences, each load-bearing: the trigger condition first, the resolve_vehicle dependency second, the mandatory safety caveat last. No filler and front-loaded with the usage cue.

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?

An output schema exists, so return values need not be described, and the description covers the trigger and prerequisite. Its only gap is behavioral disclosure (read-only nature, data freshness) that would matter more given the absence of annotations.

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 schema already states each field is a slug from resolve_vehicle with examples, so the description's mention of exact slugs largely repeats structured data. Baseline 3 is appropriate since the schema does the heavy lifting.

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?

The description makes clear this retrieves recalls/safety campaigns for a vehicle, and the phrase 'asks specifically about recalls' implicitly contrasts with the broader sibling get_known_issues. It stops short of an explicit verb+resource statement or naming the sibling it excludes, so it is clear but not maximally differentiated.

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?

It gives a concrete triggering condition ('when the user asks specifically about recalls or safety campaigns') and a prerequisite ('requires exact slugs from resolve_vehicle'), which routes the agent to resolve_vehicle first. It does not state when NOT to use it or contrast it directly with get_known_issues.

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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