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BACH-AI-Tools

Vehicle Database MCP Server

year

Retrieve available vehicle warranty years to check coverage eligibility and expiration dates for North American and European vehicles.

Instructions

Provides a list of years available for vehicle warranty year.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoExample value: warranty
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 states the tool provides a list, implying a read-only operation, but doesn't cover aspects like authentication needs, rate limits, error handling, or the format of the returned list. 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, clear sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and efficiently conveys the essential information, 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 the tool's apparent simplicity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, or output format. For a tool in a complex server with many siblings, more context would be beneficial, 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?

The input schema has one parameter ('data') with 100% description coverage in the schema ('Example value: warranty'). The description adds no additional meaning about parameters, such as explaining what 'data' represents or how it affects the output. With high schema coverage, the baseline is 3, as the schema handles the 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: 'Provides a list of years available for vehicle warranty year.' It specifies the action ('provides a list'), resource ('years'), and context ('for vehicle warranty year'), which is clear and specific. However, it doesn't explicitly distinguish this tool from sibling tools like 'year_2', 'years', or 'years_2', which might offer similar year-related functionality, so it doesn't reach the highest 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or specific contexts for usage. Given the many sibling tools (e.g., 'year_2', 'years', 'vehicle_warranty'), this lack of differentiation leaves the agent without clear direction on tool selection.

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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