Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish read-only, idempotent, non-destructive behavior, so the description only needs to add methodological nuance. It does so by disclosing 2026 INSS/IRRF tables, the incidence of discounts, and that indemnity-related verbas are exempt. The description is consistent with the annotations and adds useful behavioral context beyond 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 dense but efficient: two sentences that front-load the domain, then enumerate components and tax treatment with no filler. Every clause contributes, including the legal reference, the 2026 tables, and the indemnity exemption note.

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 complex tool with nine parameters, no output schema, and zero parameter descriptions, this description provides a solid high-level overview but not enough operational completeness. It omits input semantics, calculation assumptions, enum behavior, and return-value shape, leaving significant gaps for an agent trying to invoke it correctly.

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%, so the description carries the burden of explaining nine parameters, but it only partially does so. It names concepts like 'férias vencidas' and 'aviso prévio indenizado', which map to some fields, but it lacks explicit guidance for `salario`, `admissao`, `demissao`, `motivo`, `saldo_fgts`, `dependentes`, and `projetar_aviso`. An agent would struggle to correctly map all inputs without additional knowledge.

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 resource: 'Verbas rescisórias / liquidação trabalhista (CLT)' and enumerates exactly what the tool computes: saldo de salário, aviso prévio, 13º proporcional, férias, FGTS penalties, and INSS/IRRF discounts. The intent is unambiguous, but it does not explicitly differentiate itself from the overlapping sibling calculo_fgts, so it misses a perfect score.

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 CLT termination context makes it fairly clear when to use this tool, and the enumerations help disambiguate it from non-labor sibling calculators. However, there is no explicit when-not-to-use guidance or alternative routing, such as directing FGTS-only cases to calculo_fgts. Usage is implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.