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fuel_calc

Compute fuel needed and trip cost from distance, consumption and price. Pure CPU, instant.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "distance": "<distance>"
    },
    "name": "fuel_calc"
  }
}

Input Schema

NameRequiredDescriptionDefault
priceNoPrice per litre or gallon
distanceYesDistance
consumptionNoFuel consumption

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed4 schema fields changed
    • addedInput schema / properties / consumption
      Added value: +{
      +  "description": "Fuel consumption",
      +  "type": "number"
      +}
    • addedInput schema / properties / distance
      Added value: +{
      +  "description": "Distance",
      +  "type": "number"
      +}
    • addedInput schema / properties / price
      Added value: +{
      +  "description": "Price per litre or gallon",
      +  "type": "number"
      +}
    • addedInput schema / required
      Added value: +[
      +  "distance"
      +]
  4. Added

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations supplied, the description does carry some behavioral weight: 'Pure CPU, instant' tells the agent there are no side effects, no network dependency, and negligible latency. It does not disclose what happens when the optional consumption or price are omitted, or what a malformed input yields, so the mutation/return behavior picture is incomplete.

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 short sentences, zero filler, with the purpose front-loaded before the performance note. Nothing is redundant or buried.

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

Completeness3/5

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

For a simple three-parameter calculator with no output schema and no annotations, the description covers the core contract adequately. It is thin on unit expectations (litres vs gallons, km vs miles) and on what the result structure looks like, both of which an agent needs to interpret the output 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 description coverage is 100%, so the schema already documents all three parameters and the baseline of 3 applies. The description restates the parameter roles (distance, consumption, price) in prose but adds no units, ranges, or defaulting behavior beyond the schema — notably it does not clarify that only distance is required.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and two concrete outputs ('compute fuel needed and trip cost') plus the three inputs that produce them, so an agent knows exactly what the tool returns. It does not differentiate itself from near-neighbours such as distance, unit_convert, or percentage_calculator, which keeps it from a 5.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance and no named alternative for related conversions or cost math. The only usage-adjacent signal is 'Pure CPU, instant', which hints this is a local calculation rather than an API call, but an agent must infer the rest from the name.

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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