vehicle_market_valueVehicle Market Value for a VIN. Accepts query parameters: odometer (int), odometer_unit (str).Pass them via 'params' dictionary.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes | ||
| odometer | No | ||
| odometer_unit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that parameters are passed via a 'params' dictionary, which is a usage detail, but does not disclose what the tool returns, whether it is a read-only operation, or any side effects or limitations. This is a significant gap.
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 short and front-loaded with the core purpose. It wastes few words, though there is a minor formatting issue ('Pass them' lacks a space after the period). It is appropriately concise but misses opportunities to add value within the limited structure.
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 three parameters with no schema descriptions, no annotations, and an output schema that is not referenced, the description is incomplete. It does not explain the expected output (e.g., market value amount and currency) or any constraints on VIN format, making it insufficient for an agent to fully understand the tool's behavior.
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 0%, so the description must compensate. It names odometer and odometer_unit but does not explain their meaning, accepted formats (e.g., units for odometer_unit), or the vin parameter. The instruction 'Pass them via params dictionary' is a technical detail, not semantic explanation.
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 identifies the resource (VIN) and the subject (vehicle market value), effectively distinguishing it from siblings like stolen_check and vin_decode. However, it lacks an explicit verb like 'retrieve' or 'calculate', relying on the noun phrase 'Vehicle Market Value for a VIN'.
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 accepting query parameters but does not specify any prerequisites, exclusions, or scenarios where this tool is preferred over sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: stolen check, market value, VIN decoding, and field listing. Even vin_decode and vin_decode_info are separate since one returns decoded data and the other returns available fields.
All tool names use lower_snake_case and are descriptive, but they mix noun-phrase patterns (vehicle_market_value) with verb-noun patterns (vin_decode). This is a minor inconsistency, though still readable and predictable.
Four tools is a well-scoped size for a vehicle data API, covering the essential VIN-related lookups without unnecessary redundancy or overwhelming breadth.
The surface covers core VIN tasks: decode, market value, stolen status, and field availability. Minor gaps like VIN validation or vehicle history reports exist but are not obvious dead ends for common use cases.