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UK Data: US vehicle safety (NHTSA)

vehicle_complaints

Read-onlyIdempotent

What goes wrong with this car? Summarises owner-filed safety complaints to NHTSA for a make, model and model year: total complaints, crashes, fires, injuries and deaths reported, the most-complained-about components, and the latest complaints with their text. For used-car buyers, owners and researchers. Source: NHTSA Office of Defects Investigation complaints. Complaints are unverified owner reports, not proven defects, and counts partly reflect how many cars were sold. (cost: 1 credit)

Input Schema

NameRequiredDescriptionDefault
makeNostring, required, vehicle make, e.g. honda
limitNointeger, optional, latest complaints to list, 1-50, default 10
modelNostring, required, US model name, e.g. accord
modelYearNointeger, required, model year, e.g. 2019

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The annotations already declare this as a read-only, idempotent, non-destructive open-world lookup. The description adds information the annotations do not supply: the data source (NHTSA ODI), a 1-credit cost, and important caveats that complaints are unverified owner reports, not proven defects, and that counts are confounded by sales volume. Those caveats matter for interpretation, but nothing is said about pagination or response shape.

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?

It is well front-loaded: a question frames the use case, then the scope, then the outputs, then caveats, source and cost. The rhetorical opening costs a few words, and the output enumeration is long, but every clause carries real information.

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?

There is no output schema, so the description has to describe the response, and it does so thoroughly: totals, crashes, fires, injuries, deaths, most-complained components and latest complaint text. It also states the source and the credit cost. Nothing an agent needs to call it correctly is missing.

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%, so the schema already documents make, model, modelYear and limit. The description mentions the make/model/year triple and that 'latest complaints with their text' are returned, which hints at what limit controls, but adds no format or constraint detail 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 names a specific resource (NHTSA owner-filed safety complaints) and the exact scope (make, model, model year), and it lists the outputs: totals, crashes, fires, injuries, deaths, top components and latest complaint text. That is enough for an agent to tell it apart from vehicle_recalls, vehicle_problem_counts and complaint_by_odi_number without opening a schema.

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

Usage Guidelines3/5

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

It names an audience ('used-car buyers, owners and researchers'), which implies when the tool is useful. However, it never says when to choose it over sibling tools that cover the same vehicle domain, such as vehicle_recalls for recall campaigns or complaint_by_odi_number for a single complaint. The 1-credit cost note is useful but not routing guidance.

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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