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VIN Decoder + Safety Recalls (NHTSA)

vin_decode

Identify a vehicle from its VIN and check for safety recalls before a purchase, listing, insurance quote or repair. Decodes a 17-character VIN with NHTSA vPIC (make, model, year, trim, body, engine, fuel, drive, transmission, plant, check-digit validation) and lists NHTSA recall campaigns for that make, model and year. Recalls are per model, not VIN-specific. Use when a VIN is all you have; coverage is best for US-market vehicles. $0.003 per call, USDC on Base (x402).

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": "vin_decode"
  }
}

Input Schema

NameRequiredDescriptionDefault
vinNo17-character Vehicle Identification Number
recallsNoInclude recalls (default true)
payment_signatureNox402 v2 PAYMENT-SIGNATURE header value. Omit to receive payment requirements.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden and does substantial work: it discloses the paid x402 flow, the $0.003 USDC-on-Base cost, and the key semantic limitation that recalls are per make/model/year rather than VIN-specific. It stops short of describing failure behavior for malformed or invalid VINs and any rate/latency expectations.

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?

Three sentences, front-loaded with the agent-relevant use case before the mechanics and cost. The parenthetical field list is dense but every clause is informative; only the pricing sentence could be considered secondary to the core call decision.

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?

With no annotations, no output schema and three parameters, the definition covers the trigger, the returned field set, the key data-quality caveat and the payment mechanic. An agent has enough to decide whether and how to invoke it without opening the schema.

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 the VIN's 17-character form and check-digit validation and clarifies that the 'recalls' flag pulls per-model campaigns, but it adds little syntax or defaulting detail beyond what the schema already states.

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?

Uses a specific verb+resource pair (decode a 17-character VIN, list NHTSA recall campaigns) and enumerates the decoded fields, so an agent knows exactly what comes back. It also names the buying/listing/insurance/repair contexts where the result matters.

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?

Gives a clear trigger ('Use when a VIN is all you have') plus a coverage caveat ('best for US-market vehicles'). There are no sibling tools, so the absence of explicit alternatives is acceptable; what's missing is any guidance on when not to call it (e.g. non-US or fleet-level lookups).

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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