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BACH-AI-Tools

Vehicle Database MCP Server

decode_2

Decode UK vehicle registration numbers to retrieve year, make, model, color, engine details, and additional vehicle information from the Vehicle Database MCP Server.

Instructions

UK registration decode API requires a valid UK registration number to return the year, make, model, color, engine details \u0026 more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regYesExample value: {reg_num}
for_api_portalYesExample value: true
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 the tool is an 'API' and requires a 'valid UK registration number', hinting at external dependencies and input validation. However, it lacks details on error handling, rate limits, authentication needs, or what '& more' includes in the output. For a tool with no annotations, this leaves significant behavioral gaps.

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 a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words, though '& more' is vague. Every part contributes to understanding the tool's function, making it appropriately concise for a simple lookup tool.

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 no annotations, no output schema, and 2 parameters with full schema coverage, the description is minimally adequate. It covers the basic purpose and input requirement but lacks details on output structure, error cases, or integration context. For a decode tool with external API dependencies, more completeness would be helpful, but it meets the minimum viable threshold.

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 parameters 'reg' and 'for_api_portal' are documented in the schema. The description adds no specific parameter semantics beyond implying 'reg' is a UK registration number. It doesn't explain the purpose of 'for_api_portal' or provide format examples. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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 the tool's purpose: 'decode API requires a valid UK registration number to return the year, make, model, color, engine details & more.' It specifies the verb ('decode'), resource ('UK registration number'), and output details. However, it doesn't explicitly differentiate from sibling tools like 'decode' or 'us_plate_decode', which likely handle different regions or formats.

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

Usage Guidelines2/5

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

The description provides minimal usage guidance: it implies use when you have a UK registration number. It doesn't specify when to choose this tool over alternatives (e.g., 'decode' for general use, 'us_plate_decode' for US plates), nor does it mention prerequisites like API access or valid registration formats. No explicit when-not or alternative recommendations are given.

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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