Calcula o décimo terceiro salário — 1ª parcela, 2ª parcela com descontos de INSS e IRRF. Parâmetros obrigatórios: salary, months_worked. Opcionais: dependents. Use exatamente estes nomes, em inglês.
| Name | Required | Description | Default |
|---|---|---|---|
| salary | Yes | Salário bruto mensal em R$ | |
| dependents | No | Dependentes para IRRF | |
| months_worked | Yes | Meses trabalhados no ano (1-12) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does disclose that both installments are calculated and that INSS/IRRF discounts are applied, which is useful. However, it omits key behavioral context such as which tax/year rates are used, rounding rules, and whether separate gross/deduction amounts are returned.
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?
Three short sentences, each earning its place: purpose, parameter requirements, and naming instruction. The most important information is front-loaded, and there is no filler.
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?
For a moderate-complexity calculation with no output schema, the description clarifies inputs and the broad result (two installments with discounts), but it does not specify the return shape, tax-table assumptions, or handling of edge cases. An agent can invoke it correctly but may be uncertain about the exact output format.
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 coverage is 100%, so the schema already documents all parameters. The description labels salary and months_worked as required and dependents as optional, which duplicates the schema; the only additional value is the instruction to use exact English parameter names.
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 uses a specific verb ('Calcula') and a precise resource ('décimo terceiro salário'), and further specifies the scope as 1ª and 2ª parcelas with INSS/IRRF discounts. This makes it clearly distinguishable from sibling salary tools like calculate_net_salary or calculate_annual_salary, even without naming them.
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 intended use is implied by the tool's purpose and the required-parameter list, but the description never states when to prefer this tool over closely related salary calculators. No explicit alternatives, exclusions, or conditions are given.
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.
