DER SP: DARE, 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 |
|---|---|---|---|
| ait | No | ||
| cnpj | 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 convey read-only and idempotent behavior. The description adds valuable context about payment (prepaid credit), legal compliance (LGPD, data controller), and the nature of data (same as available to citizen, not confidential). This goes beyond the 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 front-loaded with the purpose and then provides context in a logical order. It is slightly verbose due to legal boilerplate, but each sentence contributes meaningful information about usage, payment, and data handling. No wasted words.
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 absence of an output schema and zero parameter descriptions, the description should clarify both inputs and expected returns, but it does not. It covers high-level aspects like source and legal context but omits technical details, leaving the agent uncertain about what data to provide and what to expect.
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?
Input schema has two parameters (ait, cnpj) with zero description coverage, and the description does not explain their meaning or usage. It never mentions cnpj or ait, leaving the agent without guidance on what values to provide. The description completely fails to compensate for the schema's lack of detail.
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's function: consulting DARE from DER SP in an official source. It uses a specific verb ('consulta') and resource ('DER SP: DARE'), and it stands apart from sibling tools like authenticate or report_bug, which are 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 provides clear context for usage: it is hosted by the platform, requires no platform credentials, is paid via prepaid credit, and accesses non-confidential official data. However, it does not explicitly name alternatives or state when not to use the tool, so it falls short of a perfect score.
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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