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lookup_cpf_realtime

Consulta um CPF brasileiro em tempo real na Receita Federal pela CPFHub.io. Retorna os dados cadastrais, a situação atual e deathYear (number | null, sempre presente). Data de nascimento divergente ou CPF inexistente na Receita retornam erro com code birth_date_mismatch ou cpf_not_found, sem cobrar créditos. Requer CPF, data de nascimento e autenticação via API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cpfYesCPF a ser consultado (apenas números ou formatado)
api_keyNoSua API key da CPFHub.io (opcional se já enviada no header x-api-key da conexão)
birth_dateYesData de nascimento no formato DD/MM/YYYY ou DDMMYYYY

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that mismatch/nonexistent CPFs return errors (birth_date_mismatch, cpf_not_found) without charging credits, that deathYear is always present, and that API key auth is required. It does not disclose rate limits, credit cost on success, or return format, but this is solid behavioral context.

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?

Four sentences, each earning its place: source, return, error behavior, requirements. Slightly dense but front-loaded with the core purpose and no filler.

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?

No output schema, but the description summarizes return fields (dados cadastrais, situação, deathYear) and error codes, and covers auth. It is complete enough to invoke correctly, though a bit more on credit cost on success or return shape would fully close the gap.

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

Parameters3/5

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

Schema coverage is 100% and all three parameters are described in the schema, including api_key's optionality and the two date formats. The description adds auth requirement context but no parameter syntax beyond what the schema provides – baseline 3 is appropriate.

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?

States a specific verb+resource ('Consulta um CPF brasileiro em tempo real na Receita Federal pela CPFHub.io') and names the data source. Distinguishes from sibling 'lookup_cpf' via 'em tempo real' (real-time vs presumably cached/batch) and 'Receita Federal', though it doesn't explicitly contrast with the sibling.

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

Usage Guidelines3/5

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

Implies usage via the real-time Receita Federal source and the required birth_date, but does not state when to prefer this over 'lookup_cpf' or 'get_quota_info'. The error conditions hint at constraints but usage context is left to inference.

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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