cars-data.com — Car Specs API
Server Details
Search, 180-spec localized specs, compare & filter over 102k+ vehicle variants, 19 languages.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.4/5 across 6 of 6 tools scored. Lowest: 2.7/5.
Each tool has a clearly distinct purpose: search_cars finds variants, get_specs retrieves detailed specs, get_images fetches images, compare_variants does side-by-side comparison, filter_cars provides structured filtering, and list_generations shows model generations. No overlap.
All tool names follow a consistent verb_noun pattern in lowercase snake_case (e.g., compare_variants, get_specs, list_generations). There are no deviations or mixed conventions.
With 6 tools, the set is well-scoped for a car specs API. It covers search, filtering, detailed specs, images, comparison, and generation history without being overly large or minimal.
The tool surface covers the core lifecycle: discovery (search_cars, filter_cars), detailed info (get_specs, get_images, list_generations), and comparison (compare_variants). There are no obvious missing operations for the domain.
Available Tools
6 toolscompare_variantsBInspect
Side-by-side localized specs for 2-4 vehicle variants.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | ||
| variant_ids | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only hints at the return type (side-by-side specs) but does not mention side effects, performance characteristics, error behavior, or localization details (e.g., how locale affects output). Minimal beyond purpose.
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, efficient sentence that front-loads key information: action, resource, and constraints. No unnecessary words; every part 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?
Given the tool's complexity (comparing 2-4 variants) and the lack of output schema, the description is too brief. It omits what 'specs' includes, return format, error handling (e.g., invalid IDs), and localization behavior. More details are needed for an agent to use it 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?
Schema description coverage is 0% (no parameter descriptions in schema). The description does not explain the 'variant_ids' format or the 'locale' enum, only implicitly indicating that 2-4 IDs are needed. It adds no semantic detail beyond the schema structure.
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 'Side-by-side localized specs for 2-4 vehicle variants' clearly states the action (compare), the resource (vehicle variant specs), the format (side-by-side), and the scope (2-4 variants). It effectively distinguishes the tool from siblings like 'filter_cars' (filtering) and 'get_specs' (likely single vehicle).
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, such as 'get_specs' for a single variant or searching. It lacks context about prerequisites, typical use cases, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
filter_carsAInspect
Structured catalog filter: fuel type, body type, drive layout, power/price range, model year, EV-only.
| Name | Required | Description | Default |
|---|---|---|---|
| ev | No | ||
| body | No | body_slug, e.g. suv, sedan, hatchback | |
| fuel | No | e.g. petrol, diesel, electric, hybrid | |
| year | No | ||
| drive | No | substring match, e.g. 'front', 'rear', 'all' | |
| limit | No | ||
| locale | No | ||
| power_max | No | ||
| power_min | No | ||
| price_max | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It lists filterable attributes but does not disclose behavior such as read-only nature, response format, or side effects. Minimal transparency beyond the filter categories.
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?
A single sentence conveys the core functionality without extraneous detail. Efficient and front-loaded.
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 10 parameters, no output schema, and no annotations, the description is too sparse. It lacks details on defaults, argument constraints, combinatory behavior, and response structure, leaving significant gaps for an agent.
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 only 30%, and the description adds value by listing filter categories (fuel, body, drive, etc.), but it does not explain all 10 parameters individually (e.g., limit, locale, power_min/max units). Partial compensation.
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 filters cars by specific criteria (fuel type, body type, etc.), using a specific verb ('filter') and resource ('catalog'). It distinguishes from siblings like search_cars by emphasizing structured filtering fields.
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 implies usage for structured filtering but does not explicitly state when to use this tool versus search_cars or other siblings. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_imagesCInspect
Image URLs (own CDN, no attribution burden) for a vehicle variant.
| Name | Required | Description | Default |
|---|---|---|---|
| variant_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'own CDN, no attribution burden' but does not disclose auth needs, rate limits, or error handling (e.g., missing variant_id).
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?
Single sentence, no redundancy, front-loaded with key info. Every word earns its place, though it is very minimal.
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, no annotations, and 0% schema coverage. The description fails to specify output format (single URL or list?), error behavior, or how variant_id maps to a variant. Highly incomplete for a data retrieval tool.
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 coverage is 0% (no description for variant_id). The description only says 'for a vehicle variant', which adds minimal meaning beyond the schema's type and required flag.
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 'Image URLs for a vehicle variant', using a specific verb ('get' implied) and resource. It distinguishes from siblings like compare_variants, get_specs, etc., which handle different data.
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 explicit guidance on when to use this tool vs alternatives. Siblings are listed but not explained. The description implies use for image retrieval but lacks exclusionary details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_specsAInspect
Full localized specs for one vehicle variant, in any of 19 languages — 180 spec types covering engine & fuel, performance, EV/hybrid, safety (30 specs), comfort & interior (47), exterior, chassis, dimensions & weights, consumption (WLTP/NEDC). Each spec carries a confidence score; the response carries last_synced_at — surface both so you don't overstate certainty.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | ||
| variant_id | Yes | from search_cars or filter_cars |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description fully bears the burden of disclosure. It reveals that each spec carries a confidence score and the response includes last_synced_at, advising not to overstate certainty. No mention of mutability, side effects, or rate limits, but the disclosed traits are valuable.
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 paragraph that front-loads the core purpose, then efficiently enumerates spec categories, and ends with a critical behavioral note about confidence scores. Every sentence adds value without redundancy.
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 output schema and no annotations, the description adequately explains what the tool returns (specs with confidence, last_synced_at) and its scope. Missing error handling or pagination info, but for a single-variant lookup with two params, this is largely sufficient.
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 coverage is 50% (variant_id has description, locale does not). The description adds that locale supports 19 languages and lists spec categories, but does not elaborate on specific parameter formats or constraints beyond what the schema provides. Baseline 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 clearly states the tool returns 'Full localized specs for one vehicle variant' with specific categories and language options. It distinguishes itself from siblings like 'compare_variants' and 'search_cars' by its singular focus on comprehensive specs.
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 implies use when detailed specs for a single variant are needed. The variant_id parameter description references 'search_cars or filter_cars', indicating data prerequisites. However, no explicit when-not-to-use or alternative tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_generationsCInspect
Generations/facelifts of a model, with production years.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | ||
| model_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only mentions what it returns (generations with production years), but does not disclose any behavioral traits like ordering, pagination, or whether it is read-only.
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?
A single, front-loaded sentence that concisely states the tool's purpose without unnecessary 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?
No output schema exists, and the description only vaguely specifies that results include production years. It lacks detail on the structure of returned data, making it hard for an agent to parse results.
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 coverage is 0%, and the description does not explain either parameter (model_id or locale). The locale enum is left entirely undocumented.
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 lists generations/facelifts of a model with production years. It distinguishes from siblings like search_cars or compare_variants, but does not specify the exact scope (e.g., all generations for a model).
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 on when to use this tool versus alternatives such as search_cars or compare_variants. Lacks any context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_carsAInspect
Free-text search across 102k+ vehicle variants, 115 brands, 19 languages. Returns candidate variant_ids to pass to get_specs/get_images/compare_variants.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | e.g. 'bmw 3 series' or 'tesla model s' | |
| locale | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions the scale (102k+ variants, 115 brands, 19 languages) and that it returns variant_ids. However, it does not disclose whether the search is fuzzy or exact, rate limits, or authentication needs, leaving some behavioral aspects unclear.
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, well-structured sentence that immediately conveys the tool's purpose and key attributes, with no unnecessary words. It is appropriately front-loaded.
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 complexity (large dataset, many languages) and no output schema, the description covers the essential aspects: what is searched, what is returned, and how results are intended to be used. It misses details like pagination or result ordering, but is fairly complete.
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 coverage is 33% (only query has a description). The description adds that the search is 'free-text' and covers 19 languages (matching locale enum), but does not elaborate on the limit parameter behavior or provide additional constraints beyond what the schema already offers.
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 it performs free-text search across a large set of vehicle variants, brands, and languages, and it specifies that it returns variant_ids for use with other tools, distinguishing it from siblings like get_specs or compare_variants.
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 explicitly states that the tool returns candidate variant_ids to pass to other tools (get_specs/get_images/compare_variants), indicating when to use it. It does not provide when-not-to-use conditions, but the context is clear.
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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