validar_cpfValidates a Brazilian CPF number by checking its check digits without accessing personal data.
Confirma se um CPF brasileiro é matematicamente válido (dígito verificador) — não consulta dado pessoal de ninguém. Pagamento real de $0.01 em USDC (Base mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| cpf | Yes | CPF brasileiro, 11 dígitos, com ou sem pontuação |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses real payment of $0.01 USDC on Base mainnet and states no personal data is consulted. Since no annotations exist, the description fully carries the burden of exposing side effects and non-effects.
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?
Two concise sentences convey purpose, scope, and cost without unnecessary detail. Every clause adds relevant information.
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?
The description covers the tool's core behavior, input format, and payment side effect. It does not specify the output shape or return value, which is a minor gap given there is no output schema.
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 single parameter 'cpf' is described with format details (11 digits, with or without punctuation), covering both type and acceptable input. Schema coverage is complete for the one parameter.
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?
Clearly states the tool validates Brazilian CPF mathematically and explicitly notes it does not query personal data. The verb 'validar' and scope are unambiguous.
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?
Description implies use when CPF validation is needed and clarifies it is mathematical-only with no data lookup. It does not explicitly compare to sibling tools, but the names make the distinction evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.