RMI — Renda Mensal Inicial (pós-reforma EC 103/2019): média dos salários de contribuição × coeficiente (60% + 2% por ano acima de 20H/15M), com piso (salário mínimo) e teto (INSS).
| Name | Required | Description | Default |
|---|---|---|---|
| sexo | Yes | ||
| teto_inss | No | ||
| media_salarios | Yes | ||
| salario_minimo | No | ||
| tempo_contribuicao_anos | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the computational behavior: it averages contribution salaries, applies a sex-dependent coefficient (60% plus 2% per year above 20 for men/15 for women), and enforces the minimum-wage floor and INSS cap. This adds meaningful behavioral context beyond the readOnly/idempotent/non-destructive annotations, though edge cases like rounding or floor/cap precedence are not addressed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire definition fits into one dense, front-loaded sentence: the concept and legal context come first, followed immediately by the formula and constraints. There is no filler, and every clause contributes to understanding the calculation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core formula, floor, and cap, which is substantial for a calculation tool, but with no output schema it does not state the return value/format, rounding behavior, or how optional floor/cap inputs are handled when absent. An agent would still need to infer some operational details before invoking it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the formula text compensates well: 'média dos salários de contribuição' maps to media_salarios, 'salário mínimo' to salario_minimo, 'teto (INSS)' to teto_inss, and '20H/15M' conveys the roles of sexo and tempo_contribuicao_anos. It does not explicitly enumerate the parameters or note which are optional/defaulted, so a perfect score is not warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the exact resource (RMI/Renda Mensal Inicial), anchors it to the post-EC 103/2019 reform, and states the calculation as average salary × coefficient with floor and cap. This formula-level specificity separates it from sibling calculators such as calculo_pensao and calculo_rmc_rcc, even without an explicit verb.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use—calculating the initial monthly benefit under the post-reform INSS rules—is clearly implied by the formula and acronym, but the description never states when to choose this tool over alternatives or what it is not for. There are no exclusion criteria or sibling references, leaving routing partially to 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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The calculo_* tools are largely distinct by legal scenario, but several overlap in mechanics—calculo_atualizar, calculo_pensao, calculo_restituicao_inss, and calculo_rmc_rcc all apply correction and interest to overdue amounts. Platform tools also blur boundaries: authenticate/connect both deal with credentials, and marketplace/toolkit_info both describe installation state.
The 16 calculation tools consistently follow a calculo_<domain> snake_case pattern, which is good. However, the 6 platform tools break the convention with single verbs/nouns (connect, marketplace, authenticate) and mixed forms (report_bug, show_version, toolkit_info), creating two inconsistent naming styles within one server.
22 tools is at the high end of reasonable for a legal-calculation suite, but the server name 'Cálculo de FGTS' suggests a much narrower scope. The platform-management tools add bulk and make the set feel broader and heavier than the name implies.
As a Brazilian legal calculation toolkit, the coverage is strong: labor, pension, criminal sentencing, family, banking, FGTS, and monetary correction are all represented. Minor gaps exist—such as no OCR extraction for FGTS statements and no standalone interest-only calculation—but the core calculation workflows are not dead-ended.