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 any behavioral traits—such as whether it's a read-only operation, what the output format looks like (e.g., list of strings or objects), if there are rate limits, or if it requires authentication. 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.

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

The description is a single, clear sentence that efficiently conveys the core purpose without any fluff. It's front-loaded with the main action ('Provides a list'), making it easy to parse. Every word earns its place, and there's no redundancy or unnecessary elaboration.

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 (a lookup tool with two parameters) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the output contains (e.g., model names, IDs, or additional data), how results are structured, or any error conditions. For a tool in a crowded namespace with many siblings, more context is needed to ensure the agent can use it effectively.

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's two required parameters. Since schema description coverage is 100% (with descriptions like 'Example value: 1999'), the schema already documents the parameters adequately. The description adds no additional semantic context—such as format expectations (e.g., year as string vs. integer) or usage notes—beyond what the schema provides, 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 market value API by a given year and make.' It specifies the verb ('provides a list'), resource ('models'), and context ('market value API'), distinguishing it from generic model-listing tools like 'models' or 'models_2'. However, it doesn't explicitly differentiate from similar market-value-related tools like 'models_market_value' (if that's a different sibling) or 'market_value_by_ymm', which slightly limits clarity.

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. With many sibling tools like 'models', 'market_value_by_vin', and 'market_value_by_ymm', there's no indication of when this specific tool is appropriate—for example, whether it's for pre-filtering before valuation or for general model lookup. This leaves the agent to guess 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.