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Decode VIN Number (NHTSA)

vehicle.vin.decode
Read-onlyIdempotent

Decode a 17-character VIN to retrieve vehicle details: make, model, year, body class, engine, fuel type, transmission, and plant country using US government open data.

Instructions

Decode a 17-character VIN — make, model, year, body class, engine, fuel type, transmission, plant country. US Government open data, unlimited, no auth (NHTSA)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vinYes17-character Vehicle Identification Number (e.g. "1HGCM82633A004352")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.5.0
  2. Removedv1.0.20
  3. Addedv1.0.15
  4. Removedv1.0.14
  5. Addedv1.0.11

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds useful context: it returns specific vehicle attributes and is from NHTSA with no auth limits. No contradictions with annotations.

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?

Two sentences: the first lists outputs, the second covers source and constraints. Extremely concise and front-loaded with essential information, no unnecessary words.

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?

Given the existence of an output schema, the description fully covers the tool's purpose, input, and usage context (government source, unlimited, no auth). No gaps for an agent to invoke this tool correctly.

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?

The schema covers the single 'vin' parameter with length constraints. The description reinforces the 17-character requirement and lists decoded outputs, adding semantic value beyond the schema for the return, but the parameter itself is well-documented.

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 states the tool decodes a 17-character VIN and lists the output attributes (make, model, year, etc.). It distinguishes from siblings like vehicle.vin.models by specifying the NHTSA source and the decode operation.

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 notes it uses US Government open data, is unlimited, and requires no auth, implying free and authoritative use for any VIN. However, it does not explicitly compare with alternatives like vehicle.autodev.vin_decode, so agents may need to infer when this is the best choice.

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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