Pisos salariais e vales-transporte cadastrados no PJe-Calc

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower; the description still adds real value by disclosing the data source (read via modelos_atualizar with alvo "catalogos") and the precondition that PJe-Calc must be stopped, plus the same-state/municipality validity constraint. It omits pagination or result-size behavior.

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?

A single dense paragraph whose purpose is front-loaded; each sentence carries actionable information (source, integration, constraint, fallback). The comma-heavy clause stacking slightly hurts scanability but nothing is truly wasted.

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's cross-tool dependencies (modelos_atualizar, verbas[].base), lack of an output schema, and no required params, the description covers return fields, downstream usage, precondition, validity constraint, and fallback. It is complete enough for an agent to call it correctly, with only minor gaps around edge cases.

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 coverage is 100%, so both parameters (uf, nome) are already documented in the schema; the description mentions uf/município in the context of results rather than clarifying the filter parameters. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb ("Lista") and resource (the "Pisos Salariais" and "Vale-transporte" tables of the user's PJe-Calc), and enumerates the returned fields (id, nome/linha, UF, município, período). It is immediately distinguishable from sibling catalogs like catalogo_cartao_ponto.

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?

Explains how the returned id is consumed (verbas[].base { tipo: "SALARIO_DA_CATEGORIA", piso: id } / { tipo: "VALE_TRANSPORTE", ... } and valorPago), which defines the tool's purpose in the workflow, and even gives a fallback when the table is absent (HISTORICO_SALARIAL). It does not, however, name explicit sibling alternatives or exclusion conditions.

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