Calcula quanto um gasto recorrente viraria se fosse investido. Ex: café de R$10/dia → quanto dá em 10 anos investido. Parâmetros obrigatórios: daily_expense. Opcionais: annual_return, years. Use exatamente estes nomes, em inglês.
| Name | Required | Description | Default |
|---|---|---|---|
| years | No | Período em anos | |
| annual_return | No | Retorno anual do investimento (%, padrão 10%) | |
| daily_expense | Yes | Gasto diário em R$ |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the disclosure burden. It transparently signals that the tool is a pure calculation ('Calcula') and hints at the output through the example, but it does not reveal the calculation assumptions, the return format, or whether the result includes the contributions. This is acceptable for a simple calculator but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core purpose, followed by a helpful example and minimal parameter guidance. Each sentence earns its place, with no filler or redundant marketing language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is sufficient for invoking the tool: it states the purpose, gives an example, and identifies required vs optional parameters. However, with no output schema and no annotations, it does not specify the exact return value, units, or compounding assumptions, leaving an agent without a complete picture of the expected response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 modest value beyond the schema: it repeats required/optional status, warns to use exact English parameter names, and illustrates daily_expense with the coffee example. It does not provide new semantic detail about parameter formats or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Calcula') and a clear resource: converting a recurring expense into the amount it would become if invested. The concrete example (R$10/day coffee → 10-year invested total) makes the tool's purpose unmistakable and distinguishes it from generic sibling calculators like calculate_compound_interest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly defines when to use the tool: whenever a recurring expense should be projected as if invested. It reinforces usage with an example and lists required/optional parameters. However, it does not explicitly say when not to use it or how it differs from similar investment/opportunity-cost siblings, stopping short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
