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Gov Fueleconomy Gov

gov_fueleconomy_gov
Read-only

US EPA fuel economy ratings from FuelEconomy.gov for a model year, make and model: each matching vehicle's EPA combined, city and highway MPG, fuel type, drive type and CO2 tailpipe grams per mile. Up to 3 vehicles per call. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesMake, e.g. Toyota
yearYesModel year, 4 digits, e.g. 2024
modelYesModel, e.g. Camry

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeNo
yearNo
modelNo
sourceNo
vehiclesNo
checkedAtNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds important behavioral details beyond them: a cap of up to 3 vehicles per call, pricing at $0.002 USDC per successful call via x402 on Base, Solana, or Arc, and no charge for failed calls. These are exactly the operational facts an agent needs before invoking a paid read tool.

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 compact and front-loaded: it states the data source, required inputs, returned fields, result cap, and pricing in a tight sequence. Every sentence carries useful information for deciding whether and how to call the tool.

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 three fully documented required parameters, an output schema, and annotations covering read-only and open-world behavior, the description supplies the remaining operationally relevant details: return fields, vehicle cap, payment model, and failure pricing. Nothing needed to invoke the tool correctly appears to be 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 description coverage is 100%, and the schema already documents make, year, and model with examples. The description confirms the same three inputs but does not add syntax, matching rules, or normalization guidance beyond what the schema provides.

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?

States a specific verb and resource: returns US EPA fuel economy ratings from FuelEconomy.gov for a given model year, make, and model. It also enumerates the returned fields, so the agent can distinguish this vehicle-fuel-economy lookup from unrelated directories and government data tools.

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?

The description implies when to use the tool by specifying that it requires year, make, and model, and returns EPA ratings for matching vehicles. However, it does not explicitly say when not to use it or name any alternative tool for vehicle data.

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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