Receita Federal: NFS-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 |
|---|---|---|---|
| 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?
Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses payment via prepaid credit, hosting by the platform without credentials, and LGPD data controller responsibilities. This adds meaningful operational and legal context beyond what annotations already provide.
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 three sentences with multiple clauses, mixing purpose, payment, and legal compliance. While front-loaded with the core purpose, the later sentences are verbose and could be condensed or moved to separate metadata. It is not overly long but not tightly concise.
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 query tool with good annotations, the description provides operational and legal context, but it omits parameter meaning and the expected return behavior. With no output schema, agents are left to infer how the data is returned (e.g., data payload, status, error codes). This is a moderate gap.
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 fails to explain the single required parameter 'chave'. It does not state what the key represents (e.g., NFS-e access key, registration number), leaving the agent without any semantic guidance. The description must compensate but does not.
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's purpose: 'NFS-e, consulta em fonte oficial' (NFS-e query in official source). It specifies the resource (NFS-e) and the source (Receita Federal), and the verb 'consulta' matches the tool name. This distinguishes it from the unrelated sibling tools like authenticate or 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 implies usage context (querying official Brazilian sources) and mentions operational prerequisites (no platform credentials, prepaid credit). However, it does not provide explicit when-to-use vs. alternatives or any exclusions. Since siblings are unrelated, this is adequate but not explicit.
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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