Hopi

Fuel cost calculator

hopi_fuel_cost_calculator

Read-onlyIdempotent

Estimate the fuel cost of a journey from the distance in miles, the car's fuel economy in miles per gallon (UK gallon) and the pump price in pence per litre. Optionally double it for a return trip and split between passengers. Returns total cost, litres used and cost per person. Costs in GBP. Source: https://hopi.co.uk/fuel-cost-calculator/

Input Schema

TableJSON Schema

Name	Required	Description
`mpg`	Yes	Fuel economy in miles per UK gallon
`miles`	Yes	One-way distance in miles
`people`	No	Number of people to split the cost between (default 1)
`returnTrip`	No	Double the distance for a return journey (default false)
`pencePerLitre`	Yes	Pump price in pence per litre

Output Schema

TableJSON Schema

Name	Required	Description
`mpg`	No
`miles`	No
`litres`	No
`people`	No
`gallons`	No
`summary`	Yes
`totalCost`	No
`source_url`	Yes	The tool's page on hopi.co.uk (cite or open to check the figure)
`costPerPerson`	No
`pencePerLitre`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026
- addedOutput schema / required
```
Added value: +[
+  "source_url",
+  "summary"
+]
```
First observedSep 20, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Beyond the annotations' read-only/idempotent hints, the description discloses UK gallon units, pence-per-litre pricing, return-trip doubling, passenger splitting, and the returned fields (total cost, litres used, cost per person). It adds meaningful behavioral context without contradicting annotations.

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?

Three tight sentences with no wasted words. The core purpose and required inputs are front-loaded, optional behaviors and outputs follow, and the source URL is cleanly appended.

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?

With a complete schema, clear annotations, an output schema, and a description that covers inputs, optional modifiers, outputs, currency, and units, an agent has everything needed to call this tool correctly. The source link adds helpful provenance.

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 all five parameters and their meanings. The description restates the role of key parameters and adds output information, but does not materially deepen parameter semantics 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 states a specific verb ('Estimate') and resource ('fuel cost of a journey'), with explicit inputs and outputs. It distinguishes this from the many sibling calculators by naming the exact computation and its optional return-trip and cost-splitting features.

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?

The description gives clear context: use this when estimating journey fuel cost from miles, mpg, and pence per litre, with optional return trip and passenger splitting. It does not explicitly name alternatives or exclusions, but the usage context is unambiguous.

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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