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VIN Decoder

VINDecoder
Read-only

VIN Decoder: VIN Decoder turns a 17-character Vehicle Identification Number into the vehicle it identifies. Returns make, model, year, trim, body class and manufacturer, plus engine specifications, plant of manufacture, and the safety equipment fitted to that specific build. Optionally adds every safety recall issued for that vehicle and its NHTSA 5-star crash-test rating. (Cost: 10 credits)

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": {
      "vin": "<vin>"
    },
    "name": "VINDecoder"
  }
}

Input Schema

NameRequiredDescriptionDefault
vinYesThe Vehicle Identification Number to decode. Partial VINs are accepted and decode as far as the available characters allow.
recallsNoAdd the safety recalls NHTSA has issued for this vehicle's make, model and year.
fuelEconomyNoAdd EPA fuel economy (city, highway and combined MPG, or MPGe for electric) for the matching versions of this vehicle.
safetyRatingNoAdd the NHTSA 5-star crash-test rating for the closest tested version of this vehicle.

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNoError message, null on success
statusNo"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The annotations already establish readOnlyHint=true, openWorldHint=true and destructiveHint=false, so safety is covered. The description adds something the annotations cannot: a concrete cost ('10 credits') and the fact that optional extras expand the result set, both of which matter for deciding whether to call it. It does not discuss rate limits or failure behavior for an invalid VIN.

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?

Roughly four sentences, front-loaded with the core transformation and then the payload list, with the cost disclosed in parentheses at the end. The only waste is the redundant 'VIN Decoder: VIN Decoder turns...' restatement of the title.

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?

For a four-parameter, read-only lookup with an output schema and full parameter documentation, the description covers purpose, return contents, optional enrichments and pricing. Enumerating return fields is somewhat redundant given the output schema exists, but it does not leave any decision-relevant gap.

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%, so the baseline is 3. The description reinforces that 'recalls' and 'safetyRating' are opt-in enrichments and ties them to NHTSA, but it never mentions the fuelEconomy flag at all and adds no syntax or format meaning beyond the schema.

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 states a specific verb and resource: 'turns a 17-character Vehicle Identification Number into the vehicle it identifies', and then enumerates exactly what comes back (make, model, year, trim, body class, manufacturer, engine specs, plant, safety equipment). Nothing about it could be confused with the other automotive siblings such as USCarModels or DTCLookup.

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 clear the tool is for decoding a VIN and that the recall, fuel-economy and crash-rating data are optional add-ons rather than defaults, which tells an agent how to configure a call. It does not name an alternative or say when not to use it, so it stops short of explicit routing guidance.

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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