SEFAZ PE: 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 mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond annotations: it is a paid per-query operation, hosted by the platform, requires no platform credentials, and returns only non-secret official data subject to LGPD controller responsibilities. No contradiction exists.
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 reasonably compact and front-loads the main purpose: 'SEFAZ PE: NFC-e, consulta em fonte oficial.' The additional payment/no-credential and LGPD context are relevant operational details, though the legal sentence adds minor length without directly impacting tool invocation.
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 main tool context reasonably well: official source, payment model, credentials, and data sensitivity. However, the absence of any explanation of the 'nfce' parameter format and the lack of an output schema description leave notable gaps for an agent selecting and invoking the tool correctly.
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 schema has a single string parameter 'nfce' with no description, and the schema description coverage is 0%. The description mentions NFC-e generally but never specifies what value should be passed—whether it is the full access key, date/full receipt code, or some other identifier—so an agent would have to infer the input format from the parameter name alone.
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 states the tool queries NFC-e data from SEFAZ PE via an official source, using a specific verb ('consulta') and a clear resource/scope. It distinguishes itself from the unrelated sibling tools by focusing on a SEFAZ-specific lookup.
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 gives practical context: no platform credentials are required, usage is billed from prepaid credit, and the data is the same public information available to citizens. It does not explicitly discuss when not to use the tool or name alternatives, but the context is clear enough for this narrow lookup tool.
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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