Recomenda o melhor regime tributário — MEI, Simples Nacional, Lucro Presumido — com base no faturamento e atividade.
| Name | Required | Description | Default |
|---|---|---|---|
| activity | Yes | Tipo de atividade | |
| has_employees | No | Tem funcionários? | |
| employee_count | No | Quantos funcionários | |
| monthly_revenue | Yes | Faturamento mensal em R$ |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention that the recommendation is advisory, what factors besides revenue and activity are considered (e.g., employees), or any limitations. The optional has_employees and employee_count parameters receive no mention, leaving their role in the recommendation opaque.
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?
A single, well-formed sentence that front-loads the action and outcome, listing the regimes and the key inputs. There is no filler or redundant information, making it highly efficient.
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 gives the core purpose and inputs but, with no output schema and no annotations, it omits what the response will look like (e.g., just the regime name or a detailed comparison). The role of optional parameters and the advisory nature of the recommendation are also unstated, leaving moderate gaps for an agent invoking this tool.
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%, setting a baseline of 3. The description adds context by naming 'faturamento e atividade' as the basis, which maps to monthly_revenue and activity. However, it does not clarify how the optional employee-related parameters factor into the recommendation; the schema descriptions are minimal as well.
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 'Recomenda' and a clear resource 'melhor regime tributário', naming the exact tax regimes (MEI, Simples Nacional, Lucro Presumido) that are compared. It clearly distinguishes itself from sibling calculate_* tools by focusing on choosing the best regime rather than computing a single tax value.
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?
No guidance is given about when to use this tool versus alternatives like calculate_simples_nacional, calculate_mei_tax, or compare_clt_vs_pj. The description implies use for regime selection but provides no exclusions, prerequisites, or routing hints.
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.
