Compara renda líquida CLT vs PJ (Simples Nacional) para o mesmo valor bruto. Inclui benefícios CLT e custos PJ. Parâmetros obrigatórios: gross_value. Opcionais: pj_tax_rate, pj_accountant. Use exatamente estes nomes, em inglês.
| Name | Required | Description | Default |
|---|---|---|---|
| gross_value | Yes | Valor bruto mensal em R$ | |
| pj_tax_rate | No | Alíquota Simples Nacional (%, padrão 6%) | |
| pj_accountant | No | Custo mensal do contador em R$ |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It usefully discloses that CLT benefits and PJ costs are included and that the comparison is on the same gross value. It does not describe the output shape or underlying assumptions, but it does not contradict any annotations.
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 short and front-loaded with the core purpose, followed by compact parameter guidance. Every sentence contributes, though the required/optional listing partially duplicates what the schema already declares.
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 tool is simple: three flat parameters, all documented in the schema, with no nested objects. The description captures the computation scope and required inputs. The main gap is the absence of any indication of the return value format, which matters since there is no output schema.
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 of 3 applies. The description repeats the parameter names and warns to use English names, which reinforces usage but adds no semantic meaning beyond the schema's own per-parameter descriptions.
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 opens with a specific verb ('Compara') and names the exact resource ('renda líquida CLT vs PJ (Simples Nacional)') under the condition 'mesmo valor bruto.' It also states what the comparison includes (benefícios CLT, custos PJ), which clearly differentiates it from single-scenario siblings like calculate_net_salary or calculate_pj_invoice.
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 scenario is implied: use this tool when comparing CLT vs PJ net income for the same gross value. However, it never names sibling alternatives such as evaluate_pj_offer or states when not to use them, so there is no explicit routing 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.
