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FalaZuki Finance BR

calculate_card_machine_fee

Calcula quanto sobra de uma venda na maquininha e qual o custo efetivo dela ao mês, juntando a taxa da adquirente com o prazo até o dinheiro cair. Compara com o custo de antecipar os recebíveis. Parâmetros obrigatórios: sale_amount, fee_percent. Opcionais: installments, days_to_receive, anticipation_rate_per_month. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fee_percentYesTaxa cobrada pela maquininha sobre a venda, em % (ex: 3.5)
sale_amountYesValor da venda passada na maquininha, em R$
installmentsNoEm quantas parcelas o cliente pagou (1 = à vista)
days_to_receiveNoDias até receber (na venda parcelada, o prazo da primeira parcela; as outras vêm de 30 em 30)
anticipation_rate_per_monthNoTaxa de antecipação por mês adiantado, em % (opcional)

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It states it is a calculation ('Calcula'), which implies a read-only operation, but it does not explicitly disclose that it has no side effects, does not require external data, or describe the output format. It does add the parameter naming directive, which is helpful, but it lacks explicit behavioral transparency expected for a mutation-free tool.

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?

The description is concise, with the primary purpose front-loaded, followed by parameter lists and a directive. It contains no fluff and every sentence contributes value. It could be slightly more compact by merging the parameter list into the schema, but it remains efficient and well-structured.

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 calculation tool with no output schema, the description explains the calculation and the comparison with anticipation, which covers the core purpose. It does not detail the return value or edge cases (e.g., what happens with defaults), but the schema provides defaults for optional parameters. The description is adequate for an agent to call the tool correctly, though not exhaustive.

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 100%, so the schema already documents all five parameters with descriptions. The description lists required and optional parameter names but adds no extra semantic meaning beyond what the schema provides. It does instruct to use exact English names, which is a minor addition, but essentially the description does not compensate beyond the baseline for full schema coverage.

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 states a specific verb 'Calcula' (calculates) with a clear resource: the net amount from a card machine sale and its effective monthly cost, plus a comparison with anticipation cost. This is precise and distinct from sibling calculate_* tools, making selection unambiguous.

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 clearly implies when to use this tool: whenever a user wants to evaluate the true cost of a card machine transaction. It does not explicitly name alternatives or exclusions, but the purpose is so specific that an agent can infer the use case. A brief mention of alternatives would improve the score.

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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