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FalaZuki Finance BR

calculate_darf

Calcula o DARF mensal de renda variável da pessoa física: ações swing trade (15%, isenção de vendas até R$ 20 mil/mês), day-trade (20%, IRRF compensável) e FIIs (20%), com compensação de prejuízo por modalidade. Opcionais: swing_result, swing_sales, swing_loss_carryforward, daytrade_result, daytrade_loss_carryforward, fii_result, fii_loss_carryforward, irrf_withheld. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fii_resultNoResultado do mês com FIIs em R$ (negativo = prejuízo)
swing_salesNoTotal de VENDAS de ações à vista no mês em R$ (régua da isenção de 20 mil)
swing_resultNoResultado do mês com ações swing trade em R$ (negativo = prejuízo)
irrf_withheldNoIRRF retido na fonte no mês (dedo-duro), compensável, em R$
daytrade_resultNoResultado do mês com day-trade em R$ (negativo = prejuízo)
fii_loss_carryforwardNoPrejuízo acumulado de FIIs em R$
swing_loss_carryforwardNoPrejuízo acumulado de swing trade de meses anteriores em R$
daytrade_loss_carryforwardNoPrejuízo acumulado de day-trade em R$

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does substantial work: it discloses tax rates, the sales exemption threshold, IRRF offset, and loss compensation by modality. It does not mention output format or edge cases, but the key computational behavior is 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?

The description is two sentences with no fluff. The core calculation is front-loaded, and the compact parameter enumeration plus the explicit 'use exactly these names' instruction 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?

The description sufficiently covers the calculation domain, tax rules, and all 8 optional input names for a tool with no output schema. The main gap is that it does not describe what the return value looks like, but the tool's purpose makes the output largely self-evident.

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 schema already documents each parameter's meaning. The description adds value by listing all parameter names and insisting they be used exactly in English, but it does not add deeper semantic details 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 names a specific verb ('Calcula') and a precise resource: the monthly DARF of variable income for individuals. It further disambiguates by enumerating the exact modalities (swing trade, day-trade, FIIs) and their respective rates, making it clearly distinct from generic sibling calculators.

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 gives clear context on when to use the tool: for monthly variable-income DARF calculation with specific rules such as the R$ 20k exemption and IRRF compensation. However, it does not explicitly state when not to use it or point to an alternative, so it falls just short of a 5.

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.

Resources