Retorna a tabela do IRPF mensal com faixas, alíquotas, deduções e o redutor da Lei 15.270/2025 (quando vigente no ano). Aceita year (2025+) pra tabela histórica.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Ano da tabela desejada (ex: 2025). Omitido, a vigente hoje. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure, and it explains both the returned data and the conditional applicability of the legal reducer. It does not cover error behavior for unsupported years, but for a read-only table lookup the core behavior is sufficiently exposed.
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 two short sentences with the main purpose front-loaded and the optional parameter guidance immediately after. There is no filler, repetition of schema content, or unnecessary detail.
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 one-parameter, read-only table lookup, the description plus schema provide enough to select and invoke the tool correctly. It enumerates what the response will contain and how to request historical data, though it could be even more complete by explicitly saying it is not a tax calculation tool or describing unsupported years.
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?
The input schema already documents the single year parameter with 100% coverage, including the default behavior 'Omitido, a vigente hoje', so the baseline is 3. The description adds historical-table context and the 2025 law cut-off, but its '2025+' phrasing is ambiguous relative to the schema's minimum of 2000, preventing a higher score.
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 'Retorna a tabela do IRPF mensal' – a specific verb and resource – and enumerates its contents: faixas, alíquotas, deduções and the Lei 15.270/2025 reducer. This clearly distinguishes it from calculation-oriented siblings like calculate_carne_leao or check_irrf_deduction, since it returns a table rather than computing a 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?
It clearly defines the main usage context: omit year to get the current table, or pass a year for the historical table. It does not explicitly name alternative tools or state when not to use it, so it misses the top score, but the intended usage is unambiguous.
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.
