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 full burden. It describes the data source (millions of sales, frequently updated) and output types (trade-in, private party, retail values), but lacks critical behavioral details such as rate limits, authentication requirements, error handling, or response format. This is a significant gap for a tool with no structured annotations.

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 verbose and repetitive, with multiple sentences reiterating the same points about market value analysis and data sources. It could be more front-loaded and concise, as phrases like 'We analyze vehicle market value data...' and 'Our database is updated frequently...' add little unique value and detract from clarity.

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 no annotations and no output schema, the description is incomplete. It lacks details on return values (e.g., structure of market value estimates), error cases, or operational constraints like rate limits. For a tool with one parameter but significant behavioral complexity, this leaves the agent under-informed about how to effectively use it.

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 the 'vin' parameter documented in the schema. The description adds context by specifying it's for vehicle market values and mentions North America, but doesn't provide additional semantics beyond what the schema already covers (e.g., VIN format requirements or examples beyond the schema's example). Baseline 3 is appropriate given high schema 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 retrieves market values (trade-in, private party, retail) for vehicles by VIN, with specific mention of the resource (vehicle market value) and scope (North America, based on sales data). However, it doesn't explicitly distinguish this from sibling tools like 'market_value_by_ymm' or 'makes_market_value', which likely serve similar purposes with different inputs.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions it's for market values by VIN, but doesn't compare it to siblings like 'by_vin' or 'market_value_by_ymm', leaving the agent to infer usage based on tool names alone without explicit context or exclusions.

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