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 describes a read-only list operation, which implies safety, but does not mention potential limitations like rate limits, authentication needs, error handling, or the format of the returned list. For a tool with no annotations, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It uses clear language and avoids redundancy, making it easy to parse quickly. Every word contributes to understanding the tool's function.

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 simplicity (2 required parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameters but lacks details on usage guidelines, behavioral traits, and output expectations. For a list tool in a context with many similar siblings, more guidance would enhance completeness.

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 parameters 'year' and 'make' documented as strings. The description adds context by specifying these are for 'YMM specifications API', but does not provide additional semantics like valid formats, examples, or constraints beyond what the schema implies. With high schema coverage, the baseline score of 3 is appropriate as the description adds minimal extra value.

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 YMM specifications API by a given year and make.' It specifies the verb ('Provides a list'), resource ('models'), and context ('YMM specifications API'), but does not explicitly differentiate from sibling tools like 'models', 'models_2', etc., which likely serve similar purposes. This makes it clear but not fully distinguished from alternatives.

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 ('YMM specifications API') but does not specify prerequisites, exclusions, or compare it to sibling tools such as 'models' or 'models_6'. 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.