Quality Gates & Iterative Workflows

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The Quality Gates skill transforms standard AI workflows into disciplined, iterative systems by introducing structured validation checkpoints. It provides battle-tested patterns for test-driven development (TDD), multi-agent consensus, and automated iteration loops that ensure code meets specific quality thresholds before proceeding. By integrating user approval gates for costs and critical operations alongside a 4-level severity classification system, it prevents low-quality work from advancing and ensures final outputs align perfectly with user expectations.

Características Principales

• 1 GitHub stars
• Automated iteration loops with configurable limits and clear exit criteria.
• Test-driven development (TDD) loops for automated fix-and-verify cycles.
• Multi-reviewer consensus patterns for cross-model validation.
• Standardized 4-level issue severity classification (Critical to Low).
• Multi-stage user approval gates for cost, quality, and irreversible operations.

Casos de Uso

• Managing high-stakes refactoring requiring multi-model consensus and final human approval.
• Implementing a TDD workflow where Claude writes tests, runs them, and iterates until they pass.
• Classifying and prioritizing bugs found during automated code reviews to focus on critical fixes.