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FalaZuki Finance BR

compare_fuel

Compara álcool e gasolina pelo custo por quilômetro rodado, usando o rendimento real do carro, e diz quanto a escolha vale em reais por mês. Também informa o que a regra dos 70% diria, e quando ela erra. Parâmetros obrigatórios: alcohol_price, gasoline_price. Opcionais: alcohol_km_per_liter, gasoline_km_per_liter, km_per_month. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
km_per_monthNoQuilometragem mensal, para converter a diferença em reais.
alcohol_priceYesPreço do álcool por litro
gasoline_priceYesPreço da gasolina por litro
alcohol_km_per_literNoRendimento no álcool, em km/l. Padrão 7, o carro médio.
gasoline_km_per_literNoRendimento na gasolina, em km/l. Padrão 10, o carro médio.

TDQS

A4.4/5.0
Behavior4/5

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

There are no annotations, so the description carries the behavioral burden. It discloses the calculation approach (cost per km, real fuel efficiency), the output value (monthly savings in reais), and the extra nuance of the 70% rule and when it fails. It does not deeply discuss edge cases, but the core behavior is clearly described.

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?

Three sentences with no filler: the first states the main purpose and method, the second adds the key secondary output, and the third lists the parameter contract. Everything is front-loaded and necessary.

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?

With no output schema and no annotations, the description satisfactorily covers what the tool computes, what it returns conceptually, and which parameters are required vs. optional. It could mention default yield assumptions, but the schema already covers those defaults, so nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by explicitly separating required from optional parameters and warning to use the exact English parameter names—useful given the Portuguese-language description. This goes just beyond restating 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 states a specific verb ('Compara') and a specific resource (álcool e gasolina), plus the exact comparison basis (custo por quilômetro rodado). This clearly distinguishes it from sibling tools like compare_investments or compare_loans without needing to open the schema.

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 for when to use the tool: whenever comparing alcohol vs. gasoline by cost per km using real car performance. It does not explicitly name alternatives or state when not to use it, but the subject matter is narrow and unambiguous enough to route an agent correctly.

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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