Calcula valor e parcelas do seguro-desemprego 2026 com base no salário e tempo trabalhado. Parâmetros obrigatórios: average_salary, months_worked. Opcionais: times_requested. Use exatamente estes nomes, em inglês.
| Name | Required | Description | Default |
|---|---|---|---|
| months_worked | Yes | Meses trabalhados nos últimos 36 meses | |
| average_salary | Yes | Média dos últimos 3 salários em R$ | |
| times_requested | No | Quantas vezes já solicitou (1ª, 2ª ou 3ª vez) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It discloses the expected output ('valor e parcelas') and the computation basis ('salário e tempo trabalhado'), but does not state whether the calculation is official/estimated or any caveats about the 2026 values. No contradiction with annotations exists.
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 its purpose. It uses four short sentences with no filler, though it does repeat parameter information that is already present in the schema.
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 straightforward calculator with no annotations and no output schema, it adequately states what the tool computes and which parameters are required/optional. It does not describe the return format in detail, but the mention of 'valor e parcelas' covers the essential outcome.
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 describes all three parameters with 100% coverage. The description adds only the required/optional distinction and emphasizes using exact English parameter names, which is useful but minimal beyond the schema.
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 and resource: 'Calcula valor e parcelas do seguro-desemprego 2026', clearly identifying the tool's output and scope. It also names the key inputs, which helps distinguish it from the many sibling calculators.
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 first sentence implies the use case: when the user needs 2026 unemployment insurance value and installments based on salary and time worked. However, it does not explicitly mention alternatives, exclusions, or when not to use this tool versus a sibling.
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.
