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joakes90

vin-decode-mcp

by joakes90

Get Model Years

get_model_years

Retrieve the model year range for any make and model pair. Enter a vehicle make and model to see the years it was produced.

Instructions

Get the model year range for a make/model pair.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesMake name (e.g. "Porsche"). Case-insensitive.
modelYesModel name (e.g. "911"). Case-insensitive.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. 'Get the model year range' indicates a read-only lookup and gives a hint about the output shape, but it does not disclose edge cases such as unsupported make/model pairs or empty results. It does not contradict any 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?

The description is a single sentence with no redundant wording. The action, resource, and scope are all present and front-loaded, which is appropriate for a tool of this simplicity.

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?

Given a simple two-required-parameter lookup, full schema descriptions, and an existing output schema, the description is mostly sufficient for an agent to select and call the tool. It lacks explicit sibling routing, but the tool's straightforward shape makes the overall definition adequately complete.

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?

The input schema already provides 100% coverage for the two parameters, including examples and case-insensitivity notes. The description adds only the general notion of a make/model pair, so it does not meaningfully go beyond the schema. Baseline 3 applies.

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 states a specific action ('Get') and a distinct resource ('model year range') scoped to a make/model pair, which differentiates it from sibling tools like get_all_makes and get_models_for_make. However, it does not explicitly name or exclude any sibling, so it stops short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'for a make/model pair' qualifier implies the intended use case, and the required parameters reinforce it. But the description gives no explicit when-to-use vs alternatives guidance, no exclusions, and no mention of related tools like get_models_for_make when only a make is known.

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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