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, implying a read-only operation, but does not cover critical aspects like authentication requirements, rate limits, error handling, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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 functionality without unnecessary words. It is front-loaded with the main purpose, making it easy to understand quickly. However, it could be slightly more structured by explicitly listing all parameters or usage contexts.

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 lack of annotations and output schema, the description is incomplete for effective tool use. It does not explain the return values (e.g., list format, data structure), error conditions, or behavioral nuances like pagination or dependencies. For a tool with three parameters and no structured output information, more descriptive context is needed to ensure reliable agent invocation.

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 description mentions parameters ('by a given year and make'), which aligns with the input schema properties 'year' and 'make'. However, it omits the 'data' parameter entirely, which is required. With 100% schema description coverage, the schema already documents all parameters, so the description adds minimal value beyond restating two of them, meeting the baseline for high coverage.

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 warranty API by a given year and make.' It specifies the verb ('Provides a list'), resource ('models'), and scope ('for vehicle warranty API'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'models', 'models_2', 'models_4', etc., which appear to be similar, so it lacks sibling differentiation.

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 provides no guidance on when to use this tool versus alternatives. It mentions the context ('for vehicle warranty API') but does not specify prerequisites, exclusions, or compare it to sibling tools such as 'model', 'models', or 'models_arket_value'. Without this, users must infer usage from the name and parameters alone.

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