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tresor4k

macalc

calculate_vat_generic

Calculate VAT, GST, or sales tax for any country using a custom tax rate. Input the amount, rate, and tax mode (before or after tax) to get the amounts before and after tax, tax amount, and rate.

Instructions

Calculate VAT/GST/sales tax for any country with custom rate. Returns: {amount_before_tax, amount_after_tax, tax_amount, tax_rate}. See list_bundles for related 'finance-universal' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesAmount
rateYesTax rate in %
modeNoht=before tax, ttc=after taxht

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).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the return object and the mode parameter (ht/ttc), but does not disclose potential side effects, rounding behavior, or confirm read-only status. Basic transparency is present but could be more thorough.

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, front-loaded with the main purpose, and each sentence adds value. The return fields and a pointer to related tools are included, with zero waste.

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?

Given the tool's low-to-medium complexity and the presence of an output schema, the description covers the purpose, return shape, and a reference to related tools. It is mostly complete, though explicit usage guidance is missing.

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% with clear parameter descriptions. The description adds context about 'any country with custom rate' and the return fields, but does not significantly enhance meaning beyond the schema. Baseline 3 applies.

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 VAT/GST/sales tax for any country using a custom rate, distinguishing it from country-specific VAT calculators among siblings. It also lists the return fields, making the purpose unambiguous.

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 usage when a custom rate is needed and references list_bundles for related calculators, but it does not explicitly specify when to use this tool over country-specific alternatives (e.g., calculate_belgian_vat). The guidance is implied but not explicit.

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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