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VIN Decode

vin_decode
Read-onlyIdempotent

Decode a 17-character Vehicle Identification Number. Offline ISO 3779/3780 structural decode (syntax, check digit, country, model year) + NHTSA vPIC enrichment (make / model / trim / body / engine / plant). Use for insurance underwriting, used-car listing validation, fleet management.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vinYes17-character VIN (case-insensitive, no I/O/Q characters per ISO 3779).
use_vpicNoWhen false, skip NHTSA vPIC enrichment and return offline-only fields.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior. The description adds value by revealing a two-tier behavior: offline ISO structural decode plus NHTSA vPIC enrichment, and by listing the families of fields returned from each tier. It does not cover failure semantics, but annotations lower the burden.

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 tight sentences: the first states the action and output scope, the second gives concrete use cases. No filler, no repetition of schema details, and the most important information is front-loaded.

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 tool with two parameters and rich annotations, the description is nearly complete: it names the input format, the two decoding layers, the output field categories, and the intended business contexts. The absence of an output schema is partially mitigated by the listed fields, though exact error/response shape is not described.

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 parameters are already fully documented. The description reuses the concept of 'NHTSA vPIC enrichment' but adds no parameter meaning beyond what the schema provides. Baseline of 3 is appropriate.

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 names a specific verb ('Decode'), a precise resource ('17-character Vehicle Identification Number'), and enumerates concrete outputs (syntax, check digit, country, model year, make/model/trim/body/engine/plant). It clearly distinguishes the tool from other validation/enrichment siblings, none of which target VINs.

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 gives explicit use cases: insurance underwriting, used-car listing validation, and fleet management. It does not name alternatives or negative conditions, but no sibling tool addresses VINs, so the usage context is sufficiently clear.

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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TDQS

B3.2/5.0
Disambiguation2/5

Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.

Naming Consistency4/5

All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).

Tool Count1/5

129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.

Completeness4/5

Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.

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