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FalaZuki Finance BR

calculate_fator_r

Calcula o Fator R do Simples Nacional: folha/receita dos últimos 12 meses, o anexo resultante (III ou V), a alíquota efetiva nos dois cenários e quanto custa por mês ficar no anexo errado. Parâmetros obrigatórios: revenue_12m, payroll_12m. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payroll_12mYesFolha de salários dos últimos 12 meses em R$, incluindo pró-labore e encargos (INSS patronal e FGTS)
revenue_12mYesReceita bruta dos últimos 12 meses (RBT12) em R$

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It makes the read-only, computational nature clear ('Calcula') and discloses exactly what results the tool produces, including the annex and cost scenarios. It omits assumptions or error behavior, but for a pure calculation tool this is reasonably transparent.

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 purposeful sentences: the first captures the core computation and outputs, the second states the required parameters and naming constraint. No filler or 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 two-parameter calculator with no output schema, the description provides enough context about inputs and the main returned insights (annex, effective rates, monthly cost). It could add precise output formatting or assumptions, but an agent can reasonably select and invoke it.

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%, and the schema already defines both parameters with units and meanings. The description reinforces that both are required and insists on exact English names, but adds little semantic information beyond the schema.

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 opens with a specific verb and resource ('Calcula o Fator R do Simples Nacional') and enumerates distinct outputs: resulting annex (III or V), effective rates in both scenarios, and monthly cost of being in the wrong annex. This clearly differentiates it from sibling calculators like calculate_simples_nacional even without naming them.

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 the use case through the subject matter (Fator R) and explicitly lists required parameter names, but it does not state when to choose this tool over siblings or provide exclusion criteria. The guidance is inferable, 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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