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by io.github.transparentpt
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cost_to_own

Estimate a car's yearly running-cost floor in Portugal — the annual IUC road tax (Imposto Único de Circulação) every owner pays, plus a plain running-cost framing. Needs engine displacement (cc), CO₂ (g/km), fuel and first-registration year. Use this to help a buyer budget the true cost of keeping a car, beyond the sticker price.

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": {
      "cc": "<cc>",
      "co2": "<co2>",
      "fuel": "<fuel>",
      "year": "<year>"
    },
    "name": "cost_to_own"
  }
}

Input Schema

NameRequiredDescriptionDefault
ccYesEngine displacement in cm³, e.g. 1200
co2YesCO₂ emissions in g/km, e.g. 120
fuelYesFuel: petrol, diesel, hybrid, phev, electric, lpg
usedNoUsed vehicle (true, default)
yearYesFirst registration year, e.g. 2016
monthNoFirst-registration month (1-12), refines the CO₂ regime

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses the 'floor' nature, the annual IUC tax, geographic scope, and required inputs, but it does not explain output format, calculation assumptions, or how optional inputs such as month and used affect the estimate.

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 tight sentences: the core purpose and scope are front-loaded, and the use-case sentence earns its place. There is no filler or repetition.

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 tax-estimation tool with no output schema and no annotations, the description should say more about what is returned and which factors drive the estimate. It communicates the domain well but leaves the 'plain running-cost framing' and output details vague.

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 baseline is 3. The description only renames the four required parameters in plain terms and adds no meaning beyond the schema, such as how month refines the CO₂ regime or how the used flag affects the result.

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 opening phrase 'Estimate a car's yearly running-cost floor in Portugal' is a specific verb + resource, and naming the IUC road tax anchors the tool precisely. It is clearly distinct from siblings like check_fair_price and search_inventory, which concern price and availability rather than ownership running costs.

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 explicit context: 'Use this to help a buyer budget the true cost of keeping a car, beyond the sticker price,' and lists the required inputs. It stops short of a 5 because it does not state when not to use the tool or name a specific alternative tool.

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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