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Val7h

dados-b3-mcp

screener

Screen B3 stocks by financial indicator ranges (ROIC, ROE, debt-to-EBITDA, Piotroski) with min/max filters. Use without filters to get the list of valid ratios.

Instructions

Filtra o universo inteiro da B3 por faixas de indicadores.

Parâmetros:
  filtros — dicionário de faixas. Cada chave é o nome de um indicador
    seguido de `_min` ou `_max`, e o valor é o número da faixa. Frações,
    não porcentagens: ROIC de 15% é 0.15.
    Exemplo: {"roic_min": 0.15, "dl_ebitda_max": 2}
    Indicadores aceitos: roic, roe, margem_bruta, margem_ebit,
    margem_liquida, dl_ebitda, cresc_receita_1a, cresc_receita_5a_cagr,
    piotroski.
    Chame SEM filtros para receber o cardápio: a lista de indicadores
    válidos e exemplos de uso.
  ano — exercício alvo. 0 (padrão) usa, para cada empresa, o último ano
    com dado disponível — que não é o mesmo ano para todas.
  limite — máximo de empresas na resposta. Padrão 100.
  chave_api — obrigatória aqui, mesmo para WEGE3, porque a consulta
    percorre todo o universo. Deixe "" para usar DADOS_B3_API_KEY.

Só entram valores SEM flag, isto é, números que passaram limpos pela
bateria de invariantes. Um indicador marcado como suspeito não é filtrado
silenciosamente: ele simplesmente não participa. Nome de indicador
desconhecido é recusado com erro, nunca ignorado.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
anoNo
limiteNo
filtrosNo
chave_apiNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses key behaviors: it filters only values without flags (clean data), unknown indicator names are rejected with errors, and it implies the operation scans the entire universe (hence API key requirement). It also explains the 'ano' parameter's behavior (not same year for all companies). However, it doesn't disclose performance implications (e.g., slow because full scan) or rate limits, but the core behavioral aspects are covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with sections for parameters and behavior. It is detailed but not excessively verbose; each sentence adds value. The front-loading of the main purpose is good, and the parameter list is formatted clearly. It could be slightly more concise in the parameter explanations, but the level of detail is necessary given zero schema coverage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 4 parameters and no output schema, the description covers the input semantics comprehensively. It doesn't describe the output format, but since there is no output schema and the tool returns a list of companies, it might be helpful to mention the output structure. However, the tool's complexity is moderate and the missing output detail is a minor gap. The description sufficiently covers all operational aspects an agent needs to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must fully document parameters. It does: explains 'filtros' with a dictionary format, provides an example, lists all 8 accepted indicators, and the 'ano' and 'limite' semantics are clear. It even documents the API key parameter's purpose and default behavior. This is exemplary compensation for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool filters the entire B3 universe by indicator ranges. It specifies the resource (B3 universe) and the action (filter by indicator ranges). It distinguishes itself from siblings like listar_empresas and indicadores_anuais by focusing on filtering across the whole universe by indicators, and mentions that it returns a 'cardápio' when called without filters, which distinguishes its behavior from other tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear guidance on when to use the tool: to filter the full universe by indicator ranges. It includes a crucial instruction to call without filters to get the list of valid indicators and examples, which serves as a self-help mechanism. However, it doesn't explicitly state when NOT to use this tool versus alternatives like 'multiplos' or 'indicadores_anuais', but the scope (entire universe vs. specific company) is implicit. It also warns about API key requirements, which helps decide when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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