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lzinga

US Government Open Data MCP

nhtsa_safety_ratings

Read-only

Search NHTSA 5-star safety ratings by vehicle make, model, and year. Returns VehicleId for each variant to access detailed safety data.

Instructions

Search NHTSA 5-star safety ratings (NCAP) by make, model, and year. Returns vehicle variants with VehicleId. Use the VehicleId with nhtsa_safety_rating_detail.

Ratings: 5 stars = highest, 1 star = lowest. Data from 1990 to present.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesVehicle make: 'honda', 'toyota', 'ford'
modelYesVehicle model: 'civic', 'camry', 'f-150'
model_yearYesModel year
Behavior3/5

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

Annotations already declare readOnlyHint=true, indicating a read-only operation. The description adds useful behavioral context such as the return of vehicle variants with VehicleId, the star rating scale, and the data timeframe (1990–present). No contradictions with annotations.

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

Conciseness5/5

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

The description is concise, with three focused sentences. The first sentence states the purpose, the second explains the output and linking to a sibling tool, and the third provides context on rating scale and data range. No extraneous content.

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 adequately explains what is returned (vehicle variants with VehicleId), how to proceed for more detail (use nhtsa_safety_rating_detail), and the meaning of ratings and data range. This is sufficient for an AI agent to use the tool correctly.

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

Parameters3/5

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

Schema coverage is 100% with parameter descriptions, so the baseline is 3. The description provides examples (e.g., 'honda', 'civic', '2008') that reinforce the schema but do not add significant new meaning beyond what the schema already states.

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 clearly states the tool searches NHTSA 5-star safety ratings by make, model, and year. It distinguishes itself from the sibling tool nhtsa_safety_rating_detail by mentioning that the VehicleId returned should be used with that detail tool.

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 provides clear context on when to use this tool (search by make/model/year) and directs the user to nhtsa_safety_rating_detail for details. It also explains the rating scale and date range. However, it does not explicitly state when not to use this tool or mention alternative tools for different purposes.

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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