Get the full history of a vehicle by VIN — every dealer it appeared at, price changes over time, days on market, whether it was sold and resurfaced elsewhere. Data with origin.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes | 17-character Vehicle Identification Number | |
| agent_id | No | Your agent identifier (claude, grok, gpt, perplexity) |
Changes observed during successful MCP inspections.
Input schema / properties / agent_idAdded value: +{
+ "description": "Your agent identifier (claude, grok, gpt, perplexity)",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It is transparent about what data will be returned — dealer history, price changes, days on market, resale events — and adds provenance context with 'Data with origin.' It does not explicitly state read-only behavior, but 'Get' communicates a non-mutating operation.
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 concise and front-loaded with the core action and resource, followed by a useful list of returned data types. The fragment 'Data with origin.' is slightly cryptic but still earns its place by signaling data provenance. No redundant filler is present.
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?
For a read-only history tool with only one required parameter and 100% schema description coverage, the description covers the essential invocation context: what to pass (VIN) and what to expect in return. It does not detail response structure or error/empty-result behavior, but the listed content dimensions give an agent enough to decide and call correctly.
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 already provides full coverage for both parameters: vin is described as a 17-character VIN and agent_id is described as an agent identifier. The description adds no parameter-level detail beyond repeating VIN, so the baseline score of 3 is appropriate.
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 uses a specific verb ('Get') with a clear resource ('full history of a vehicle by VIN') and enumerates concrete content types: dealer appearances, price changes, days on market, and resale/resurfacing. This clearly distinguishes it from siblings like cars_vehicle or cars_search, which are likely current-listing or search-oriented.
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 clear context for when to use this tool: when a complete historical record for a vehicle identified by VIN is needed. It stops short of explicitly naming alternatives or stating when not to use it, but the 'full history by VIN' framing makes the intended use case unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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