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cliwant

mcp-sam-gov

by cliwant

nhtsa_recalls

Read-only

Look up vehicle safety recalls by make, model, and year to find manufacturer campaigns, affected components, consequences, and remedies.

Instructions

Look up NHTSA vehicle safety RECALLS for a specific vehicle — the manufacturer's recall campaigns with the affected component, the safety consequence, the remedy, and 'do not drive'/'park outside'/over-the-air-update flags (NHTSA /recalls/recallsByVehicle; api.nhtsa.gov). KEYLESS — no API key is required or accepted. Input: make (required, e.g. 'honda'), model (required, e.g. 'accord'), modelYear (required, 4-digit, e.g. '2020'). Returns { recalls:[{ campaignNumber, manufacturer, component, summary, consequence, remedy, reportReceivedDate, parkIt, parkOutside, overTheAirUpdate }] } + honest _meta. HONESTY: totalAvailable is NHTSA's EXACT Count and NHTSA returns the COMPLETE set for the vehicle (no pagination) ⇒ complete:true; a no-match (Count 0 / a bad make/model) ⇒ an HONEST EMPTY (returned:0), NOT an error; a 4xx ⇒ invalid_input; a 5xx/timeout ⇒ THROWS; a 200 non-JSON ⇒ schema_drift. The park-it/park-outside/over-the-air-update flags are preserved as booleans (never a fabricated false); dates are strings; every scalar is null-never-empty-string. Fixed host api.nhtsa.gov (SSRF-guarded); make/model are letters/digits/space/hyphen only and modelYear is ^\d{4}$.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesVehicle make (required), e.g. 'honda', 'ford'. Letters/digits/space/hyphen only (^[A-Za-z0-9 -]+$).
modelYesVehicle model (required), e.g. 'accord', 'f-150'. Letters/digits/space/hyphen only (^[A-Za-z0-9 -]+$).
modelYearYes4-digit model year (required), e.g. '2020'. Validated ^\d{4}$.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes beyond annotations by detailing honesty guarantees (complete:true, no pagination, empty instead of error, boolean flags preserved as is), error handling (4xx vs 5xx vs 200 non-JSON), and input validation (regex patterns). This adds significant context beyond the readOnlyHint and openWorldHint annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long but well-structured with clear sections for behavior, input, output, and honesty. Every sentence adds necessary detail, though some redundancy with the schema exists.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description fully specifies the return structure and field semantics (dates as strings, null vs empty string, boolean flags). It also covers all edge cases and error modes, making the tool's behavior fully predictable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes all three parameters with 100% coverage. The description reinforces the validation patterns and adds examples, providing marginal added value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb-noun pair ('Look up NHTSA vehicle safety RECALLS') and immediately clarifies the tool's resource and domain. It distinguishes from sibling tools like 'nhtsa_complaints' by specifying safety recalls rather than complaints.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states that no API key is required ('KEYLESS — no API key is required or accepted'), which is a key usage guideline. It also details the required input parameters. However, it does not explicitly mention when not to use this tool or provide alternatives among siblings.

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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