SEFAZ PI: NFC-e, 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 |
|---|---|---|---|
| nfce | 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. The description adds valuable behavioral context beyond annotations: hosted by the platform, no platform credentials needed, pay-per-query with prepaid credit, data is not confidential, and the client is the data controller under LGPD. This meaningfully informs the agent about authentication, cost, and data responsibility.
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 core purpose and uses four concise sentences, each adding relevant context: official source, hosting/payment, data classification, and LGPD responsibility. It is slightly dense but not wasteful.
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?
For a simple one-parameter tool with good annotations, the description covers purpose, source, payment, credentials, and data privacy. However, it lacks input format guidance for 'nfce' and does not describe expected output or error behavior, which leaves some ambiguity for an agent invoking the tool.
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%, so the description must compensate for explaining the 'nfce' parameter. It only implies that the parameter is an NFC-e identifier from the tool name and first sentence, but it does not specify the expected format, length, or any constraints. This is a significant gap for correct invocation.
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 clearly identifies the tool as a consultation of NFC-e through the official SEFAZ PI source, using a specific verb ('consulta') and resource ('NFC-e'). It also distinguishes itself from unrelated sibling tools like authenticate, connect, and marketplace by focusing on official tax document consultation.
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 context for use: it queries official Brazilian sources available to citizens, requires no platform credentials, and is paid via prepaid credit. It does not explicitly name alternatives or exclusions, but the sibling tools are unrelated, so the usage context is sufficient.
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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