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 the tool as providing a list, which implies a read-only operation, but doesn't address key behavioral aspects such as error handling, rate limits, authentication needs, or what happens if parameters are invalid. For a tool with no annotations, this leaves significant gaps in understanding how it behaves beyond basic functionality.

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, straightforward sentence that efficiently conveys the core purpose without unnecessary details. It's front-loaded with the main action and context, making it easy to parse. However, it could be slightly more structured by explicitly listing parameters or usage scenarios, but it avoids waste and is appropriately concise for its purpose.

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 complexity of a tool with 3 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., format of the list), error conditions, or how it integrates with the 'vehicle maintenance API' context. For a tool in a server with many siblings, more contextual detail is needed to ensure the agent can use it effectively without confusion.

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 each parameter ('year', 'make', 'data') documented with example values. The description adds minimal semantic value beyond the schema, as it only reiterates that parameters are 'by a given year and make' and mentions 'data' implicitly. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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 maintenance API by a given year and make.' It specifies the verb ('provides a list'), resource ('models'), and context ('for vehicle maintenance API'), which is clear and specific. However, it doesn't explicitly distinguish this tool from sibling tools like 'models', 'models_2', etc., which appear to be similar, so it doesn't reach the highest score of 5.

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 maintenance API') but doesn't specify when to choose this tool over sibling tools such as 'models' or 'decode', nor does it outline any prerequisites or exclusions. This lack of comparative usage information limits its effectiveness for an AI agent.

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