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BACH-AI-Tools

Vehicle Database MCP Server

us_decode

Decode 17-digit VINs to retrieve vehicle specifications including year, make, model, trim, engine details, drivetrain, and fuel type for US and Canada vehicles from 1981 to 2024.

Instructions

This API provides basic specifications including year,make.model, trim, engine specs, drivetype and fuel types of any vehicle. Note: Works for all 17 digit VINs based on US and Canada regions and having coverage from 1981 to 2024.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vinYesExample value: 1B3AL46XX6N227698
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions regional coverage (US/Canada) and date range (1981-2024), which adds useful context. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, error handling, or what happens with invalid VINs.

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?

The description is appropriately sized with two sentences. The first sentence states the purpose clearly, and the second adds important constraints. There's no wasted text, though it could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 1 parameter with 100% schema coverage but no annotations and no output schema, the description provides adequate basic information about what the tool does and its constraints. However, for a tool with no annotations or output schema, it should ideally provide more behavioral context about what to expect from the response.

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% with the parameter 'vin' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema. With high schema coverage, the baseline is 3 even without additional parameter semantics in the description.

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 clearly states what the tool does: 'provides basic specifications including year, make, model, trim, engine specs, drivetype and fuel types of any vehicle.' It specifies the verb ('provides') and resource ('vehicle specifications'), but doesn't explicitly distinguish it from similar sibling tools like 'decode', 'vin_decode', or 'by_vin'.

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 description implies usage context by stating it 'Works for all 17 digit VINs based on US and Canada regions and having coverage from 1981 to 2024.' However, it doesn't explicitly say when to use this tool versus alternatives like 'decode', 'vin_decode', or 'by_vin', nor does it provide any exclusion criteria.

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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