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BACH-AI-Tools

Vehicle Database MCP Server

years_5

Retrieve available years for vehicle recall data to access specific recall information by year.

Instructions

Provides a list of years available for vehicle recall 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 states the tool provides a list, implying a read-only operation, but doesn't cover aspects like rate limits, authentication needs, error handling, or the format of the returned list. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 efficiently conveys the core function without unnecessary details. It's front-loaded with the main action and resource, making it easy to parse. There's no wasted verbiage, and every word contributes to understanding the tool's purpose.

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 simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks details on the return format, error conditions, or integration with sibling tools. For a basic list-fetching tool, it meets the bare minimum but doesn't provide full context for reliable use.

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 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain any parameters, which is appropriate. It implicitly suggests no inputs are required to fetch the list of years, aligning with the schema. A baseline of 4 is given since no parameters exist, and the description doesn't add or contradict parameter info.

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 recall API.' It specifies the action ('provides a list'), resource ('years'), and context ('for vehicle recall API'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'years', 'years_2', etc., which likely serve similar purposes, preventing 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. It doesn't mention prerequisites, such as needing to call this before other recall-related tools, or compare it to siblings like 'years' or 'vehicle_recall'. Without any usage context, the agent must infer when this tool is appropriate.

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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