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BACH-AI-Tools

Vehicle Database MCP Server

years_2

Retrieve available years for vehicle data queries to support VIN decoding, history checks, and specifications lookup in North America and Europe.

Instructions

Provides a list of years available for Advanced Decode API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool provides a list, implying a read-only operation, but does not specify any behavioral traits such as rate limits, authentication requirements, or what the output format looks like. For a tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence that directly states the tool's function: 'Provides a list of years available for Advanced Decode API.' It is front-loaded with the core purpose and contains no unnecessary words, making it highly concise and well-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 that the tool has zero parameters and no output schema, the description adequately covers the basic purpose. However, it lacks details on behavioral aspects (e.g., output format, any constraints) and does not differentiate from sibling tools, which reduces completeness. It meets the minimum viable standard but has clear gaps in providing full context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema description coverage is 100%, so there is no need for parameter details in the description. The description appropriately focuses on the tool's purpose without redundant parameter information, earning a high score as it adds value by explaining what the tool does rather than repeating schema details.

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: 'Provides a list of years available for Advanced Decode API.' It specifies the verb ('Provides a list') and resource ('years'), making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'year', 'year_2', 'years', 'years_3', etc., which might offer similar year-related data, so it falls short of a perfect score.

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 offers no guidance on when to use this tool versus alternatives. With multiple sibling tools related to years (e.g., 'year', 'years', 'years_3'), there is no indication of what makes 'years_2' distinct or when it should be preferred. This lack of context leaves the agent without clear usage instructions.

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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