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Cost Per Mile to Own a Car Calculator

cost_per_mile_calculator

Cost Per Mile to Own a Car Calculator — See what your car truly costs to drive: enter yearly fuel, maintenance, insurance, depreciation, and financing interest or lease cost to get your real cost per mile driven.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fuelYes
insuranceYes
annualMilesYes
maintenanceYes
depreciationYes
financingOrLeaseCostYes

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It transparently lists inputs and output, but it does not disclose the exact calculation method, handling of edge cases (e.g., zero miles), or whether all inputs are in the same currency/period. It is a simple calculator, so a 3 is appropriate—adequate but not rich in behavioral detail.

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?

The description is a single, well-structured sentence that front-loads the tool's purpose and efficiently lists inputs and output. Every word earns its place without redundancy.

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 6-parameter calculator with no output schema and no annotations, the description is mostly complete: it tells users what to enter and what to expect. It could be improved by explicitly stating annualMiles and the output format (e.g., dollars per mile), but the core information is present and sufficient for an agent to select and invoke the tool.

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 0%, so the description must compensate. It explains the cost categories (yearly fuel, maintenance, insurance, depreciation, financing/lease cost) and implicitly references annualMiles via 'cost per mile driven.' This adds meaning to the parameter names, especially 'financingOrLeaseCost.' However, it does not explicitly name annualMiles as a parameter or clarify units for all fields, so a 4 is warranted.

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 clearly states the tool calculates the true cost per mile to own a car, listing all key input categories (fuel, maintenance, insurance, depreciation, financing/lease) and the output (cost per mile driven). This specific verb+resource distinguishes it from sibling car-related calculators like car_loan_calculator or car_depreciation_calculator.

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 when to use it—when you have yearly cost figures and want overall cost per mile—but it does not explicitly state alternatives or exclusions. It lacks guidance such as 'for loan-only calculations use car_loan_calculator.' The context is clear enough to infer usage, but the lack of exclusions keeps it at a 3.

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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TDQS

B3.1/5.0
Disambiguation2/5

Many calculators occupy overlapping conceptual spaces, such as 'ai_roi_calculator' vs 'ai_automation_payback_calculator' and 'llm_self_host_vs_api_calculator' vs 'ai_build_vs_buy_calculator'. The boundaries between debt payoff, savings goal, and drawdown tools are also fuzzy, making it easy for an agent to select the wrong tool despite detailed descriptions.

Naming Consistency5/5

Every tool follows the same <topic>_calculator pattern with lowercase snake_case, making the naming highly predictable and consistent. Even acronyms and numbers fit the pattern, so there is no mixing of conventions.

Tool Count1/5

122 tools is an extreme number for a single MCP server, far exceeding the 50+ threshold for a severe mismatch. The tools span unrelated domains like AI costs, pet food, concrete, pizza dough, and turkey cooking, creating an unfocused kitchen-sink surface that overwhelms an agent's selection process.

Completeness3/5

The set covers many common calculator categories such as finance, construction, health, and AI costs, but several staple calculators are missing (e.g., BMI, tip, discount, simple interest, currency conversion). The AI cost cluster is over-saturated while other everyday calculations are absent, leaving minor but noticeable gaps.

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