Receita Federal: Agenda Tributária, 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 |
|---|---|---|---|
| ano | Yes | ||
| mes | 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 indicate the tool is read-only, idempotent, and non-destructive, so the description does not need to repeat these. The description adds useful context about payment requirements (pre-paid credits) and data privacy (LGPD), but does not detail potential limitations like data availability delays or rate limits.
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 sentence that packs multiple pieces of information (official source, hosting, payment, data privacy) but lacks structure. It front-loads the tool's purpose but then mixes compliance and payment details, making it slightly dense. No unnecessary repetition, but could be better organized.
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 is simple (2 params, read-only, no nested objects), the description covers key operational aspects. However, it does not explain the output format or any potential error conditions (e.g., invalid month/year), which could affect usability. The lack of an output schema increases the need for description clarity, but the description is adequate for basic use.
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 only defines 'mes' and 'ano' as strings without any description of expected formats (e.g., 'MM' vs 'January' or 'AAAA' vs 'YY'). The description provides no additional guidance on parameter values, leaving agents to guess the format. Since schema coverage is 0%, the description should compensate but does not, resulting in a baseline score of 3 due to the minimal parameter count.
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 as consulting the Brazilian Federal Revenue's tax calendar from an official source. It distinguishes itself from generic tools but does not explicitly contrast with any sibling that might offer similar tax data.
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 tax schedule information, but it does not specify when to use this tool versus alternatives, as there are no sibling tools with similar functionality. It also does not mention any prerequisites beyond having pre-paid credits.
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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