Vehicle data for AI: VIN decoder, automotive specs, stolen checks, valuation and way more.
Check if a VIN appears in supported police/Vincario stolen databases.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It indicates a read-only lookup (via 'check if') and notes the limited database coverage ('supported police/Vincario'), but it does not explain what happens for invalid VINs, not-found results, or whether any side effects exist. This is minimal but non-contradictory.
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 front-loaded sentence with no unnecessary words. It efficiently conveys purpose and scope in about 10 words.
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 tool's simplicity (one required parameter) and the presence of an output schema, the description sufficiently covers the core purpose and data source. It might benefit from noting that 'supported' implies limited coverage or that this is a theft-specific check, but overall it is adequate for the tool's low complexity.
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?
With schema coverage at 0%, the description needed to compensate by explaining the 'vin' parameter. It only repeats the concept of a VIN without adding format constraints, examples, or clarifying that the parameter is the exact identifier to search. The schema itself provides only a string type, so the description adds little meaning.
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 ('check') and names the exact resource ('VIN against police/Vincario stolen databases'), which clearly differentiates it from sibling tools like vin_decode and vehicle_market_value. It is not a tautology and immediately conveys the tool's function.
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 clearly implies the tool is for verifying theft status and limits its scope to 'supported' databases, giving useful context. However, it does not explicitly name alternatives or say when not to use it, so it lacks formal exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Vehicle 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 |
|---|---|---|
| result | Yes |
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.
Decode a VIN and return detailed information about the vehicle.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral transparency. It only mentions that it returns detailed information but doesn't describe error handling, data format, or any side effects, which is insufficient for a tool that processes potentially malformed input.
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 sentence with no wasted words, making it easy to parse. However, this brevity comes at the cost of necessary detail, but for conciseness dimension, it is efficient.
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 presence of sibling tools and the lack of annotations, the description is incomplete. It doesn't clarify what sets it apart from vin_decode_info, nor does it explain the output structure or any prerequisites.
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 has one parameter with no description (0% coverage), so the description must compensate. It merely restates that the tool decodes a VIN, which doesn't add meaningful detail about the expected format, constraints, or validation rules.
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 and returns vehicle information, using a specific verb and resource. However, it doesn't differentiate from the sibling tool vin_decode_info, which may have overlapping functionality.
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 about when to use this tool versus alternatives like stolen_check or vehicle_market_value. The description alone gives no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List which fields are available for decoding a given VIN (free endpoint).
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It discloses that this is a 'free endpoint' and that it lists fields (not actual decoded values), which clarifies its read-only, informational nature. It does not mention return format or any limitations, but the output schema exists and the tool is simple enough that this is acceptable.
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, information-dense sentence. It front-loads the action ('List') and the target ('fields'), with a useful parenthetical about being a free endpoint. There is no wasted wording or repetition.
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 tool with one parameter, sibling context, and an output schema, the description is adequately complete. It clearly states what the tool does and that it is free. It could explicitly mention that this is a metadata endpoint for vin_decode, but the sibling tool names and the tool name itself (vin_decode_info) imply this relationship, so completeness is strong.
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 mentions 'for a given VIN', which clarifies the single 'vin' parameter's purpose and adds meaning beyond the bare type 'string'. It does not specify VIN format or validation rules, but the name 'vin' is highly self-explanatory, so this is adequate.
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 'List' and a clear resource: 'fields available for decoding a given VIN'. It distinguishes itself from sibling tools like vin_decode (which likely performs the actual decoding) by explicitly stating it lists available fields rather than decoding the VIN itself.
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 phrase 'List which fields are available for decoding a given VIN' implies this is a precursor to vin_decode, providing clear context for when to use it. However, it does not explicitly name alternatives or state when not to use it, though the sibling tool names make the distinction obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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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.
