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Search companies

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Read-onlyIdempotent

Search Brazilian companies by a term (q) and/or filters (f, a JSON string). tipo picks what the term matches: nome (legal name), fantasia (trade name), socio (partner), telefone (phone with area code), email (the full address on record), endereco (address) or cnae (activity code). Needs a term or at least one filter: a search with neither would scan 71 million establishments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fNoFilters as a JSON string.
qNoSearch term, 2 to 120 characters.
ufNoLimits the search to one Brazilian state (two-letter code, such as SP).
pageNoPage number, starting at 0.
tipoNoWhat the term matches: nome|fantasia|socio|telefone|email|endereco|cnae.
pageSizeNoResults per page, 1 to 50.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • changedInput schema / properties / f / description
      Previous value: -"JSON string de filtros"New value: +"Filters as a JSON string."
    • changedInput schema / properties / page / description
      Previous value: -"Página, começando em 0."New value: +"Page number, starting at 0."
    • changedInput schema / properties / pageSize / description
      Previous value: -"Resultados por página, de 1 a 50."New value: +"Results per page, 1 to 50."
    • changedInput schema / properties / q / description
      Previous value: -"Termo de busca, entre 2 e 120 caracteres."New value: +"Search term, 2 to 120 characters."
    • changedInput schema / properties / tipo / description
      Previous value: -"nome|fantasia|socio|telefone|email|endereco|cnae"New value: +"What the term matches: nome|fantasia|socio|telefone|email|endereco|cnae."
    • changedInput schema / properties / uf / description
      Previous value: -"Restringe a uma unidade da federação."New value: +"Limits the search to one Brazilian state (two-letter code, such as SP)."
  2. Changed1 schema field changed
    • changedInput schema / properties / tipo / description
      Previous value: -"nome|fantasia|socio|telefone|endereco|cnae"New value: +"nome|fantasia|socio|telefone|email|endereco|cnae"
  3. Changed1 schema field changed
    • addedInput schema / properties / tipo
      Added value: +{
      +  "description": "nome|fantasia|socio|telefone|endereco|cnae",
      +  "type": "string"
      +}
  4. Changed6 schema fields changed
    • addedInput schema / properties / page / default
      Added value: +0
    • addedInput schema / properties / page / description
      Added value: +"Página, começando em 0."
    • addedInput schema / properties / pageSize / default
      Added value: +20
    • addedInput schema / properties / pageSize / description
      Added value: +"Resultados por página, de 1 a 50."
    • addedInput schema / properties / q / description
      Added value: +"Termo de busca, entre 2 e 120 caracteres."
    • addedInput schema / properties / uf / description
      Added value: +"Restringe a uma unidade da federação."
  5. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds useful behavioral context beyond them: the input requirement and the performance cost of a termless, filterless scan, which is exactly the kind of operational detail annotations don't carry.

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

Conciseness5/5

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

Three front-loaded sentences with no padding: purpose first, the `tipo` semantics second, the input precondition last. Every clause carries information the agent can act on.

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 no output schema, the description would ideally say something about result shape or pagination, but `page`/`pageSize` are self-documenting in the schema and the core invocation requirements are fully covered. It is complete enough to call correctly without being exhaustive about returns.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description goes further by spelling out the semantic meaning of each `tipo` value (legal name, trade name, partner, phone, email, address, activity code) rather than just listing the enum. It also clarifies that `f` is a JSON string. That is genuine added meaning over the schema.

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

Purpose4/5

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

States a specific verb and resource ('Search Brazilian companies') and scopes it by term and/or filters. It is clear and specific, but it never names or distinguishes itself from siblings like search_construction, get_cnpj, or consulta_cadastro, so an agent gets no routing signal from the text alone.

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?

Gives a concrete usage precondition: it 'needs a term or at least one filter,' with the consequence of omitting both ('would scan 71 million establishments'). That is strong when-to-use context, but it offers no when-not-to-use exclusions or named alternatives, keeping it below a 5.

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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