Check U.S. NHTSA vehicle safety recall campaigns by make, model, and year. Live official data.
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Average 4.5/5 across 1 of 1 tools scored.
With only one tool, there is zero risk of confusion between tools. The tool's purpose is clearly defined and distinct by being the sole operation available.
The single tool name 'check_vehicle_recalls' follows a clear verb_noun pattern, which is internally consistent and predictable.
Having only one tool feels overly thin and insufficient for a server that could reasonably support multiple recall-related operations. The scope appears too narrow, earning a low count appropriateness score.
The domain of vehicle safety recalls is only partially covered. The tool only supports make/model/year queries and explicitly lacks VIN-specific lookup, which is a significant gap for a recall-checking service.
check_vehicle_recallsCheck vehicle safety recalls (NHTSA)ACheck U.S. NHTSA safety recall campaigns for a vehicle by make, model, and model year. Returns official NHTSA recall campaigns (component, hazard, remedy, campaign number, official notice link) plus the date the data was fetched. Results are model-year campaign matches, NOT VIN-specific repair status — an empty result means no open recalls were found in NHTSA as of the returned date, which is not a guarantee the vehicle is safe.
| Name | Required | Description | Default |
|---|---|---|---|
| make | Yes | Vehicle make, e.g. Honda, Ford, Toyota | |
| year | Yes | Four-digit model year, e.g. 2021 | |
| model | Yes | Vehicle model, e.g. Civic, F-150, Camry |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond the readOnlyHint and openWorldHint annotations by explaining exactly what data is returned (campaigns with component, hazard, remedy, number, notice link), that results are as of the fetched date, and that an empty result is not a safety guarantee. This provides meaningful behavioral context beyond annotations.
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 two sentences, every phrase earns its place, and the most important information is front-loaded. It efficiently covers purpose, return contents, data source, and caveats without fluff.
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 simple read-only tool with fully documented parameters and no output schema, the description fully covers what is returned, the freshness date, and key limitations. It is complete for the tool's complexity, especially with annotations providing the read-only/open-world context.
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 100%, so the schema already fully documents all three parameters. The description does not add parameter-specific details or formatting guidance beyond the examples in the schema, staying at the baseline for well-schemaed params.
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 states a specific action ('Check U.S. NHTSA safety recall campaigns') on a clear resource (vehicle by make/model/year) and explicitly distinguishes itself from VIN-specific recall status checks. This is a specific verb+resource+scope that fully clarifies what the tool does.
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?
It clearly indicates the tool is for model-year campaign matches and explicitly states it is NOT VIN-specific, which serves as a when-not-to-use guideline. It also sets expectations about empty results and data freshness, though it names no alternative tools or explicit when-to-use conditions.
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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