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Estimate CO₂ from fuel burned

estimate_fuel_burn
Read-onlyIdempotent

Estimates the CO₂ from burning an amount of aviation fuel: avgas 100LL, mogas (motor gasoline) or Jet A, in US gallons, liters or kg. Uses the US EPA factor per US gallon and the fuel’s density for liters and kg.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fuelYesThe fuel burned
unitYesUS gallons, liters or kg
amountYesHow much fuel, in `unit`

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kgYeskg of CO₂, rounded
fuelYes
unitYes
amountYes
tonnesYes
pageUrlYesThe page that explains the factor
dataUpdatedYesWhen the fuel figures last changed
kgCo2PerUsGalYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful methodology beyond annotations: it specifies the US EPA factor per gallon and density-based conversion for liters and kilograms. It does not disclose precision, rounding, or error behavior, but those are minor for a deterministic read-only estimator.

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?

Two sentences, front-loaded with the core action and scope. The second sentence supplies the calculation basis without padding, and every clause earns its place.

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 output schema exists and annotations already declare the safety profile, the description needs only to explain the estimation scope and method. It does so completely: inputs (fuel type, amount, unit) and the conversion approach are covered, and return values are handled by the output schema.

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?

Schema description coverage is 100%, so the baseline is 3. The description expands the fuel enum values (e.g., 'avgas 100LL', 'mogas (motor gasoline)', 'Jet A') and clarifies the unit handling and conversion basis, adding meaning beyond the schema's bare enum labels.

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 ('Estimates'), resource ('the CO₂ from burning an amount of aviation fuel'), and enumerates the supported fuel types and units. This clearly distinguishes it from sibling tools like estimate_flight_hours, which address a different estimation task.

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 usage when you need to estimate CO₂ from a known fuel quantity, but it never explicitly says when to use this tool versus alternatives (e.g., estimate_flight_hours). No exclusions or prerequisites are given, leaving usage to inference.

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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