Receita Federal: IRPF, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| cpf | Yes | ||
| year | No | ||
| birthdate | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds meaningful extra context: no platform credentials are needed, each query is paid with prepaid credit, the data is official and not confidential, and the client is the LGPD controller. This goes beyond the structured annotations without contradicting them.
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 front-loaded with the tool's purpose and then adds concise operational, legal, and data-governance context. Each sentence contributes meaningful information, though the LGPD sentence is somewhat verbose for an MCP tool description.
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?
There is no output schema and no parameter documentation, so the description should at least indicate what the consultation returns and what inputs are required. It provides good legal/cost framing but leaves core invocation semantics underspecified.
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?
Schema description coverage is 0%, and the description does not explain the meaning, format, or required status of cpf, birthdate, or year. Since three parameters exist and two are required, the description should compensate for the missing schema descriptions, but it does not mention any of them.
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 states the tool performs 'consulta' of 'IRPF' from the 'Receita Federal' using official sources, giving a specific verb and resource. It does not explicitly describe the exact result returned, but it is clearly differentiated from the unrelated sibling tools like authenticate and marketplace.
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 description provides clear operational context: it is hosted by the platform, requires no platform credentials, costs prepaid credit per query, and returns only non-confidential official data. It does not explicitly name alternatives or exclusions, but the context is sufficient because the sibling tools are unrelated.
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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