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FalaZuki Finance BR

calculate_raise_vs_inflation

Compara um aumento salarial com a inflação do período, no LÍQUIDO: calcula o salário líquido antigo com as tabelas de INSS e IRRF da competência antiga, o atual com as de hoje, corrige pela inflação acumulada e devolve o ganho ou perda REAL de poder de compra em % e em R$/mês, além do bruto que apenas empataria (útil para saber quanto falta pedir). Parâmetros obrigatórios: previous_gross, previous_date, current_gross, accumulated_inflation_percent. Opcionais: dependents. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dependentsNoNúmero de dependentes para dedução do IRRF, nas duas pontas
current_grossYesO salário bruto mensal ATUAL, em R$
previous_dateYesA competência do salário antigo (aaaa-mm-dd). Decide as tabelas históricas; cobertura desde 2007-01-01.
previous_grossYesO salário bruto mensal ANTES do aumento, em R$
accumulated_inflation_percentYesIPCA acumulado entre as duas competências, em % (20 = 20%). Obtenha em /v1/rates/history ou na calculadora de inflação.

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 behavioral disclosure burden. It is transparent about the calculation approach: recomputing old and current net salaries from INSS/IRRF tables, applying accumulated inflation, and returning real gain/loss plus break-even gross. It does not mention failure modes or data-coverage caveats, but none are suggested by the calculator's read-only nature.

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 sentences carry a lot of specific information without padding: the first front-loads the core purpose and output, the second gives an actionable parameter checklist. Every sentence earns its place.

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 5-parameter financial calculator with no output schema, the description explains the key return values (real % and R$/month gain/loss, break-even gross) and the inputs. It could be more explicit about the output object shape and coverage/error behavior, but schema already documents formats and IPCA source.

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%, so the baseline is 3; the description adds only the required/optional distinction and the instruction to keep English parameter names, which does not introduce semantic detail beyond the schema. No new meaning about formats, units, or derivation is added.

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?

The description clearly identifies a specific verb+resource pair (compares a salary raise against period inflation) and adds precise scope: net value, INSS/IRRF tables, real purchasing-power gain/loss in % and R$/month, plus break-even gross. It doesn't explicitly differentiate from siblings such as calculate_required_raise or calculate_real_salary, though the 'no LÍQUIDO' and table-based methodology strongly imply a unique calculation.

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 a clear use case ('útil para saber quanto falta pedir') and states required vs optional parameters and exact English names. It does not, however, name sibling tools or state when not to use it, so it falls short of explicit alternative 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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TDQS

B3.2/5.0
Disambiguation2/5

Many tools are clearly distinct, but the set contains several near-identical clusters: calculate_dividend_income_goal and calculate_dividend_yield both answer 'how much capital is needed to reach a dividend income target', and calculate_real_salary, calculate_raise_vs_inflation, and calculate_salary_time_value overlap heavily on salary/inflation comparisons. Generic tools like compare_investments and compare_with_cdb also blur the boundary with the many specific yield calculators.

Naming Consistency3/5

Most tools follow a clear verb_noun snake_case pattern with verbs like calculate_, get_, check_, compare_, and advise_. However, the object language is inconsistent (calculate_ganho_capital_imovel alongside calculate_car_affordability), and can_i_quit_job breaks the command-style pattern with a question.

Tool Count1/5

At 114 tools, the server is extremely over-scoped for an MCP surface; an agent cannot reasonably hold all these options in context. The inclusion of a search_calculator tool to route among the others is a strong signal that the tool set itself needs partitioning.

Completeness4/5

The surface is very comprehensive for Brazilian personal finance: employment, taxes, investments, debt, real estate, vehicles, small business, insurance, and market-data queries are all covered. A few minor gaps exist, such as no dedicated generic boleto-fine calculator or consolidated investment comparison engine, but no core workflow feels badly stranded.

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