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MaCalculatriceEnLigne

calculate_car_lease_vs_buy

Compare leasing vs buying a car over the same period. Use for automotive purchase decisions. Inputs: car price, lease monthly cost, loan rate, ownership years. Returns total costs and recommendation. See list_bundles for related 'finance-universal' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
car_priceYesCar purchase price EUR
loan_rateYesLoan annual rate percent
loan_monthsYesLoan duration months
lease_monthsYesLease duration months
lease_monthlyYesMonthly lease payment EUR
residual_valueYesCar residual value at lease end EUR

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
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 states 'Returns total costs and recommendation' which clarifies the output but does not disclose potential side effects (e.g., data storage or mutation). For a calculator, this is minimally adequate.

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 two sentences plus a brief reference to list_bundles, with no superfluous words. Every sentence conveys essential information.

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

Completeness2/5

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

Given 6 required parameters and the presence of an output schema, the description fails to list all key inputs (missing residual_value and loan_months) and includes an extraneous parameter (ownership_years). The return value is mentioned but not fully detailed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are documented in the schema. However, the description inaccurately mentions 'ownership years' which is not in the schema, and it omits 'residual_value' and 'loan_months'. This misalignment reduces clarity.

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 uses specific verbs ('Compare leasing vs buying') and clearly identifies the resource (car purchase decision). It distinguishes from siblings by mentioning related calculators via 'list_bundles'.

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 explicitly states 'Use for automotive purchase decisions' and directs users to see list_bundles for related calculators. It lacks explicit when-not-to-use guidance but provides sufficient context.

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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