SINTEGRA: MA, 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 |
|---|---|---|---|
| ie | No | ||
| cpf | No | ||
| cnpj | No |
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 read-only, idempotent, non-destructive behavior. The description adds valuable context: hosting by platform, no platform credentials needed, pay-per-query with prepaid credit, data is not confidential, and LGPD responsibilities. This goes beyond annotations without contradicting them.
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 concise two-sentence paragraph that front-loads the primary purpose ('SINTEGRA: MA, consulta em fonte oficial') and adds critical context (payment, legal) without unnecessary detail. Every sentence provides essential information.
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 low-complexity tool with no output schema, the description covers purpose, payment, and legal aspects adequately. However, it lacks any explanation of the query parameters, which are essential for correct usage, leaving the description incomplete for effective tool invocation.
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 three undocumented parameters (ie, cpf, cnpj) with 0% description coverage. The description does not explain their purpose, how to use them, or that they are alternative identifiers. With no parameter guidance in either the schema or description, the agent cannot know how to populate the query correctly.
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 performs a consultation ('consulta') of official SINTEGRA data for Maranhão ('MA'). It specifies the resource (official Brazilian sources) and distinguishes it from sibling tools like authenticate or report_bug, which serve different purposes.
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 ('consulta em fonte oficial', 'disponível ao cidadão') but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or mention alternative tools for similar queries. Since sibling tools are platform-level rather than similar data lookup tools, the guidance is only implicit.
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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