Vehicle Database MCP Server

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 but doesn't describe output format, pagination, error handling, rate limits, or authentication needs. For a tool with no annotation coverage, this is a significant gap in transparency about how the tool behaves beyond its basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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 words. It's front-loaded with the main purpose. However, it could be slightly more structured by explicitly naming the parameters or output, but it remains highly concise and effective.

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

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

Given the tool's low complexity (2 required parameters, no nested objects) and 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks details on behavioral aspects like return format or error conditions. For a simple lookup tool, it meets basic needs but doesn't provide full context for reliable agent use.

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

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

The input schema has 100% description coverage, with both parameters ('year' and 'make') documented in the schema. The description mentions these parameters ('by a given year and make') but doesn't add any semantic details beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 models available for vehicle recalls API by a given year and make.' It specifies the verb ('Provides a list'), resource ('models'), and context ('for vehicle recalls API'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'models', 'models_2', etc., which appear to serve similar functions, 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.

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 sibling tools (e.g., 'models', 'model', 'makes') or provide context for choosing this specific tool over others in the list. This lack of comparative information leaves the agent without clear usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.