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 mentions the tool 'provides a list' but doesn't specify output format (e.g., JSON array, pagination), error handling, rate limits, or authentication requirements. For a tool with no annotations, this leaves significant gaps in understanding how the tool behaves in practice.

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 states the tool's purpose without unnecessary details. It is front-loaded and easy to parse, though it could be slightly more structured (e.g., by explicitly mentioning parameters). Overall, it earns its place with zero waste.

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 sibling tools and lack of annotations or output schema, the description is incomplete. It doesn't clarify how 'makes_3' differs from other 'makes' tools, what the output looks like, or any behavioral traits. For a tool in a crowded namespace with no structured support, more context is needed to guide effective usage.

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?

Schema description coverage is 100%, with both parameters ('year' and 'data') documented in the schema. The description adds minimal value beyond the schema by implying the tool is for 'vehicle warranty API', but it doesn't explain parameter meanings (e.g., why 'data' is required and set to 'warranty', or the format for 'year'). Baseline 3 is appropriate since the schema handles most of the documentation.

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 makes available for vehicle warranty API by year.' It specifies the verb ('provides'), resource ('list of makes'), and context ('vehicle warranty API by year'). However, it doesn't explicitly differentiate from sibling tools like 'makes', 'makes_2', 'makes_4', etc., which appear to serve similar functions, leaving some ambiguity about when to choose this specific tool.

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 multiple sibling tools (e.g., 'makes', 'makes_2', 'makes_4'), there is no indication of what distinguishes 'makes_3' from others, such as different data sources, scopes, or API versions. This lack of context makes it difficult for an agent to select the correct tool without trial and error.

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