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Calculadoras laborales y tributarias PY/EC

Calculadora de IVA Paraguay y Ecuador

calcular_iva
Read-onlyIdempotent

Agrega o saca el IVA de uno o varios montos. Ecuador (SRI): 15 % general, 5 % materiales de construcción, 0 %; redondeo a centavos. Paraguay (DNIT, Ley 6380/19): 10 % general, 5 % canasta/medicamentos/alquiler de vivienda, exento; IVA incluido = precio ÷ 11 o ÷ 21, en guaraníes enteros. Devuelve base, IVA y total por línea y por tasa, con la norma de cada tasa. Devuelve también las fuentes oficiales y el link a la calculadora web.

Input Schema

NameRequiredDescriptionDefault
modeYesadd = los montos NO incluyen IVA (agregar IVA); extract = los montos YA incluyen IVA (sacar el IVA).
linesYesLíneas de la factura (1 a 50).
countryYesPaís: py = Paraguay (guaraníes, DNIT/MTESS/IPS), ec = Ecuador (USD, SRI/IESS).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description still adds real behavioral detail beyond them: currency-specific rounding (cents in Ecuador, whole guaraníes in Paraguay), the ÷11 / ÷21 included-tax formula, per-line and per-rate output aggregation, the legal norm attached to each rate, and that official sources plus a web calculator link are returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four front-loaded sentences with no filler, leading with the operation and then the per-country specifics. The rate enumeration (15/5/0 and 10/5/ex) duplicates the schema's enum text and could be trimmed without losing information.

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?

There is no output schema, and the description compensates by describing the return shape (base, IVA, total per line and per rate, plus the applicable norm and official sources). Nothing an agent needs in order to invoke this 3-parameter, all-required tool correctly is missing.

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 coverage is 100% with rich enum descriptions, so the baseline is 3; the description earns an extra point because the 'precio ÷ 11 o ÷ 21' rule clarifies what the extract mode actually computes, which the schema does not state. It largely repeats the rate table already documented in the enum descriptions.

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?

States a concrete verb pair ('agrega o saca el IVA') plus the resource (montos/facturas) and the two jurisdictions (Paraguay DNIT, Ecuador SRI). This is unmistakably distinct from the sibling calculators (aguinaldo, horas extras, renta, retenciones, multas), so an agent can route without opening the schema.

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 conveys clear usage context: which countries and which statutory rates apply, and the add-vs-extract semantics are spelled out (reinforced by the schema enum). It does not explicitly state when to pick this tool over a sibling or any exclusion (e.g. non-VAT taxes), leaving that to obvious domain inference.

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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