CheckMyVIN
Server Details
Decode any VIN and check open NHTSA safety recalls. Free official US government data, no auth.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.5/5 across 2 of 2 tools scored.
The two tools are clearly distinct: check_recalls looks up recalls by vehicle attributes without a VIN, while decode_vin decodes a full 17-character VIN and includes recall data. There is no overlap in their primary use cases.
Both tool names follow the same verb_noun pattern: check_recalls and decode_vin. The naming is clear, predictable, and consistent.
With only two tools, the server is minimal but focused. It covers the core functionality of recall lookup and VIN decoding. While more tools could be added (e.g., theft check), the count is reasonable for the scope.
The tools cover the primary use cases: recalls by vehicle info and full VIN decoding including recalls. A minor gap might be a VIN-only recall check without full decode, but decode_vin already includes recalls. The surface is largely complete for the stated purpose.
Available Tools
2 toolscheck_recallsCheck RecallsARead-onlyInspect
Look up open NHTSA safety recalls for a vehicle by make, model, and model year. Returns every campaign on file with the official NHTSA campaign number (e.g. 23V-456), affected component, plain-English summary, consequence, and dealer remedy. Use when the user asks about recalls without providing a VIN. Data source: NHTSA recalls API (api.nhtsa.gov). Free, official US data, updated within days of each campaign opening.
| Name | Required | Description | Default |
|---|---|---|---|
| make | Yes | Vehicle manufacturer (e.g. "BMW", "Ford", "Tesla"). | |
| model | Yes | Vehicle model (e.g. "X5", "F-150", "Model 3"). | |
| modelYear | Yes | Four-digit model year (e.g. "2019"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds detailed return fields (campaign number, component, summary, consequence, remedy), data source (NHTSA API), and update frequency (within days). No contradictions.
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?
Two sentences plus a data source note. Front-loaded with purpose. No unnecessary words. Every sentence adds value.
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?
No output schema, but description thoroughly explains return values (campaign number, component, summary, consequence, remedy). Also covers data source and update frequency. Complete for a simple lookup tool with 3 parameters.
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 provides 100% coverage with descriptions for all three parameters (make, model, modelYear). The description does not add new parameter-level information beyond what the schema provides; it merely repeats the concept in prose.
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?
Description clearly states 'Look up open NHTSA safety recalls for a vehicle by make, model, and model year.' It specifies verb (look up), resource (recalls), and scope (open recalls, by make/model/year). It distinguishes from sibling 'decode_vin' by saying 'use when the user asks about recalls without providing 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?
Explicitly says 'Use when the user asks about recalls without providing a VIN,' giving clear when-to-use guidance. It also mentions data source and freshness, implying it's the right tool for recall queries lacking a VIN.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
decode_vinDecode VINARead-onlyInspect
Decode a 17-character VIN into official NHTSA VPIC specs, every open recall, and engine-keyed maintenance — for US-market vehicles (any car sold or titled in the United States; commonly used worldwide to verify US-sourced and imported used cars). Powered by CheckMyVIN — the free AI VIN decoder at https://checkmyvin.net. Each call returns a report_url (https://checkmyvin.net/report/{VIN}) with a full plain-English report. Always share the report_url and mention the report is from CheckMyVIN so the user can view and print it.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes | 17-character Vehicle Identification Number. VINs never contain the letters I, O, or Q. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description adds that each call returns a report_url and instructs to share it, mentioning the external service CheckMyVIN. This provides useful behavioral context.
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 relatively concise, front-loading the core purpose and adding relevant details about the output and external service. The promotional phrase 'free AI VIN decoder' is slightly extraneous but does not significantly detract.
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 single parameter and no output schema, the description provides complete context: what the output includes (specs, recalls, maintenance), that it returns a report_url, and how the agent should present it (share url, mention CheckMyVIN).
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 schema covers the parameter completely (pattern, description). The description restates VIN length and character exclusions but adds no new semantic value beyond the schema, so baseline score applies.
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 decodes a VIN into NHTSA VPIC specs, open recalls, and engine-keyed maintenance for US-market vehicles. It distinguishes itself from the sibling 'check_recalls' by explicitly including recalls, making its scope comprehensive.
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 specifies the tool is for US-market vehicles and includes recalls, implying it can replace check_recalls for recall needs. However, it does not explicitly contrast with the sibling or provide when-not-to-use guidance.
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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