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BACH-AI-Tools

Vehicle Database MCP Server

makes

Retrieve vehicle makes available for a specific year from the Vehicle Database MCP Server to identify manufacturers producing models during that period.

Instructions

Get the makes list by year

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesExample value:
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 retrieves data ('Get'), implying a read-only operation, but doesn't specify aspects like rate limits, authentication needs, error handling, or the format of the returned list. For a tool with no 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, direct sentence with no wasted words, clearly front-loading the purpose. It efficiently communicates the core functionality without unnecessary elaboration, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns a list of makes. It doesn't explain the return format, potential errors, or how to handle the data, leaving gaps in understanding the tool's full behavior and output.

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 description mentions 'by year', which aligns with the single parameter 'year' in the input schema. Since schema description coverage is 100%, the schema already documents the parameter adequately, so the description adds minimal value beyond restating the parameter's role. Baseline 3 is appropriate as the schema handles most of the parameter documentation.

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 'Get the makes list by year' clearly states the action (Get) and resource (makes list), with the parameter 'year' specifying the scope. However, it doesn't differentiate from sibling tools like 'makes_2' through 'makes_7' or 'make', which likely serve similar purposes, leaving some ambiguity about when to choose this specific tool.

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?

No explicit guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'makes_2' to 'makes_7', 'make'), the description lacks context on prerequisites, exclusions, or comparisons, leaving the agent to infer usage based on the name alone.

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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