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Glama

Babá Certa

Calcular salário líquido

calcular_salario_liquido
Read-only

Estima o salário líquido mensal de uma babá a partir do salário bruto, dependentes e vale-transporte informados. Retorna INSS, IRRF, transporte, fontes e premissas. Não presume dados da conta nem interpreta vínculos individuais.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dependentesNo
diasUteisMesNoDias úteis no mês; se não informado, 22.
salarioBrutoYesSalário bruto mensal em reais.
valeTransporteDiarioNoCusto diário de vale-transporte em reais; se não informado, zero.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
caveatYes
statusYes
messageYes
sourcesYes
basisYearYes
breakdownYes
dependentesYes
diasUteisMesYes
salarioBrutoYes
valeTransporteDiarioYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare a safe, non-destructive, closed-world read, so that burden is lifted. The description adds genuine behavioral context: it is a pure estimator that does not presume account data or interpret individual employment links, and it discloses the returned components (INSS, IRRF, transporte, fontes, premissas). It doesn't cover rounding, tax-table year, or precision caveats.

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?

Three tight sentences: purpose first, output contents second, scope exclusion last. No filler, though the return-field sentence partially duplicates the output schema.

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 stateless calculation tool with an output schema present, the description covers purpose, inputs, statelessness, and scope limits, which is enough to call it correctly. Minor missing pieces: the diasUteisMes parameter is neither named nor hinted at, and no note on tax-year assumptions.

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 coverage is 75% and three of four parameters carry inline descriptions (defaults of 22 workdays and zero transport are documented in the schema). The description restates the main inputs but adds no format, default, or edge-case meaning beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (estima) and resource (salário líquido mensal de babá) plus the inputs it consumes, which lets an agent separate it from display siblings like mostrar_salario_liquido. It does not explicitly name a sibling or contrast with calcular_custo_baba, so it stops short of a 5.

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?

Usage is implied (compute payroll from supplied gross wage/dependents/transport) and the closing clause rules out account-derived or per-contract interpretation, which hints at scope. However, it never states when to prefer this over calcular_custo_baba or mostrar_salario_liquido, so an agent must infer the routing.

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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