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AFR Lambda Converter

convert_afr_lambda
Read-only

Convert AFR and lambda across gasoline, E85, methanol, and race fuel scales. Calculates from measured inputs without authentication and does not read or save account data. Use this as a conversion reference. Tune targets depend on fuel, engine, load, and calibration strategy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afrYesAFR
fuelYesFuel scale
lambdaYesLambda

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
noteNo
toolYesTuneWorks MCP tool name that produced this result.
inputsNo
resultNo
statusYesResult status such as ok, created, updated, sent, auth_required, or confirmation_required.
messageNo
resultsNo
unitSystemNo
volumeUnitNo
authenticationRequiredNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds useful context beyond that: no authentication required and no account data is read or saved, plus the caveat that tune targets depend on external factors. Return format is left to the output schema.

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?

Three short sentences, front-loaded with the conversion scope before caveats. Every sentence carries some weight, though the disclaimer about tune targets could be trimmed slightly without losing meaning.

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

Completeness4/5

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

For a simple, side-effect-free conversion utility with an output schema and full annotation coverage, the description supplies what an agent needs: scope, safety posture, and a usage caveat. Nothing critical is missing, though it could state the conversion direction or expected input scale.

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%, so afr, lambda, and the fuel enum are already documented in structured fields, establishing baseline 3. The description adds no format or constraint detail (e.g., scale ranges or units) beyond what the schema provides. It also does not clarify why both afr and lambda are simultaneously required.

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?

Names a precise verb and resource ('Convert AFR and lambda') and enumerates the supported scales (gasoline, E85, methanol, race fuel), which cleanly separates it from nearby siblings like calculate_ethanol_blend or calculate_race_fuel_and_weight. An agent can identify the tool's job without opening the schema.

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?

'Use this as a conversion reference' gives a clear context, and the final sentence implicitly warns that tune targets require additional engine/load/calibration context rather than this tool alone. It never names an explicit alternative tool or a hard when-not condition, so it stops short of a 5.

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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