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FalaZuki Finance BR

calculate_car_ownership_cost

Calcula o custo mensal real de ter um carro — IPVA, seguro, combustível, manutenção, depreciação, estacionamento. Parâmetros obrigatórios: car_value. Opcionais: monthly_km, fuel_price, km_per_liter, parking, car_wash, rideshare_per_km, has_financing, monthly_financing. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
parkingNoEstacionamento por mês em R$. Zero se você não paga.
car_washNoLavagem por mês em R$
car_valueYesValor FIPE do carro em R$
fuel_priceNoPreço do litro de combustível em R$
monthly_kmNoKm rodados por mês
km_per_literNoConsumo em km/litro
has_financingNoEstá financiado?
rideshare_per_kmNoPreço médio do quilômetro no aplicativo em R$, para a comparação com não ter carro.
monthly_financingNoParcela do financiamento em R$

TDQS

B3.4/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden. It discloses the tool's scope and inputs, but does not state the output format (e.g., a single monthly total vs. a breakdown) nor the assumptions for IPVA, depreciation, maintenance, or insurance rates. These are meaningful gaps for a calculation 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 two sentences: the first front-loads the core purpose and components, the second covers required/optional parameters and a naming caveat. It is efficient and free of fluff, though the parameter enumeration is partially redundant with the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a 9-parameter calculator with no annotations and no output schema, the description adequately conveys what it computes and which inputs are required. However, it does not explain the output format or the underlying cost model assumptions, so an agent may still be unsure what a successful invocation returns or how inputs influence results.

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?

The schema already describes all 9 parameters with 100% coverage, so the description adds little beyond restating names and required/optional status. The instruction to use exactly these names in English is a useful minor guard, but no deeper semantics are provided beyond the schema.

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 begins with a clear verb and object: 'Calcula o custo mensal real de ter um carro' (calculates the real monthly cost of owning a car), followed by a concrete list of cost components. It is specific and unambiguous, but it does not explicitly name sibling tools like calculate_car_affordability or compare_fuel to highlight differentiation.

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?

The intended usage is implied through the purpose statement, and the parameter list gives some context. However, there is no explicit 'use this when' / 'use that instead' guidance, no mention of alternatives, and no exclusions, so an agent gets little help choosing among the many sibling calculator tools.

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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