SEFAZ SP: Cupom Fiscal Eletrônico (SAT) - Detalhado, 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 declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds valuable context: it's hosted by the platform, requires no platform credentials, is pay-per-query with prepaid credits, and clarifies data is not confidential. It also addresses LGPD compliance, which is useful behavioral context beyond annotations.
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 a single paragraph but packs essential information: what it does, source, hosting, credentials, pricing, data nature, and LGPD. It's somewhat dense but not verbose. Could be slightly more structured, but it's efficient.
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?
Given the tool's simplicity (1 param, no output schema), the description covers the key aspects: purpose, data source, access method, and legal context. It doesn't describe return format, but with no output schema, that's a minor gap. The description is adequate for an agent to understand what this tool does and its constraints.
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 coverage is 0% and there's only one parameter 'chave' (key). The description doesn't explain what 'chave' means (likely the CF-e access key), but with a single parameter and the tool name indicating CF-e consultation, the meaning is fairly inferable. However, the description could have explicitly stated that 'chave' is the CF-e access key.
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 official SEFAZ SP source for detailed Electronic Fiscal Receipt (SAT) information. It distinguishes itself by specifying 'Detalhado' (detailed) and 'consulta em fonte oficial', though it doesn't explicitly contrast with sibling tools (which are mostly unrelated).
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 implies usage for querying official Brazilian tax data, and mentions it's the same data available to citizens, but doesn't explicitly state when to use this vs alternatives or when not to use it. Sibling tools are unrelated, so no direct comparison is provided.
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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