Content
88%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a model of lean, actionable instruction: a diff-driven tool map, concrete runner commands, and a tightly sequenced close-out loop with explicit failure handling and stopping rules. The only weaknesses are deferral of check details to external files and one vaguely signaled reference.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean with zero padding: every line is either an instruction, a tool mapping, or a labeled pointer ("Fonte da verdade (não copie o texto dessas páginas; abra e sega)") and it assumes Claude's competence throughout. | 5 / 5 |
Actionability | Concrete commands (`python3 scripts/agent_loop.py`, `apm run lint/test/audit`) and a specific diff-to-tool map (Ruff, mypy, Bandit, gitleaks, pip-audit, Trivy) plus a routing rule to `schemathesis-api`; minor gap in that check arguments and thresholds are deferred to external `loop.yaml` and docs not shown here. | 4 / 5 |
Workflow Clarity | The 8-step close-out sequence has explicit validation checkpoints and feedback loops: constrained failure feedback (`propriedade_quebrada`, `contraexemplo_minimo`), discard on repeated failure hash, a hard 3-iteration limit, and closure only when failures pass and prior passes hold. | 5 / 5 |
Progressive Disclosure | A concise overview points one level deep to clearly labeled sources (`docs/qualidade-seguranca.md`, `docs/agent-delivery-loop.md`, `loop.yaml`), but `docs/papers-research.md` is cited only as "Fonte extra" with no stated relevance, and none of the referenced files ship in the skill's own bundle. | 4 / 5 |
Total | 18 / 20 Passed |