SEFAZ SP: Cupom Fiscal Eletrônico (SAT), 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 |
|---|---|---|---|
| chave | 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, and the description adds meaningful context beyond those annotations: no platform credentials are needed, billing is per-query prepaid, and the data is non-confidential and available to citizens. The LGPD note also clarifies data-handling 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 purpose is front-loaded and the first two sentences are efficient. The later sentences about official data and LGPD responsibilities add context but are somewhat tangential to actually invoking the tool, making the description slightly less concise than it could be.
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, read-only tool, the purpose and authentication/billing context are well covered. However, there is no output schema and the description does not describe the returned data or the expected 'chave' format, leaving some uncertainty for the agent about invocation and results.
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 input schema has a single 'chave' string with zero description coverage, and the description does not explain what 'chave' should be or its expected format. The meaning is inferable from the tool's domain, but the description adds no parameter-level value.
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 names the exact resource ('Cupom Fiscal Eletrônico (SAT)') and the action ('consulta em fonte oficial') with a specific scope (SEFAZ SP). This clearly differentiates it from the unrelated sibling tools about authentication, connectivity, and platform functions.
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 clear operational context: the tool is hosted by the platform, requires no platform credentials, and is paid per query with prepaid credit. It does not explicitly state when to prefer this over alternatives or provide exclusion conditions, so it falls short of full usage guidance, but the context is clear.
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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