How does multi-reviewer consensus work?

It aggregates evaluations from multiple AI models to identify unanimous, strong, or majority agreement on specific code issues, helping prioritize fixes based on model confidence.

Can I use this for Test-Driven Development (TDD)?

Yes, the skill includes specialized patterns for automated loops that write tests, execute them, analyze failures, and iterate on the code until all tests pass successfully.

What is a Quality Gate in Claude Code?

A Quality Gate is a checkpoint in an AI workflow where execution pauses for validation, testing, or user approval before proceeding to the next step to prevent low-quality work from advancing.

What severity levels are used for issue classification?

It utilizes a standardized four-level system: CRITICAL (must fix immediately), HIGH (major bugs), MEDIUM (minor bugs/quality issues), and LOW (style and polish).

How does this skill handle cost management?

It provides patterns for cost gates that calculate estimated expenses and present them to the user for approval before running expensive multi-model operations or large-scale refactors.

Quality Gates

Name: Quality Gates
Author: MadAppGang

byMadAppGang

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177

Productividad y Flujo de Trabajo

Implements structured validation checkpoints, automated iteration loops, and user approval workflows to ensure high-quality AI outputs.

Acerca de

The Quality Gates skill provides robust patterns for managing complex AI workflows by introducing critical checkpoints before execution proceeds. It empowers developers to build iterative refinement systems that include cost-conscious user approval gates, automated test-driven development (TDD) loops, and sophisticated issue severity classification. By utilizing multi-reviewer consensus and structured feedback loops, this skill transforms standard 'fire and forget' prompts into reliable, production-ready engineering processes that consistently meet quality and safety standards.

Características Principales

Standardized 4-level issue severity classification (CRITICAL to LOW)
Multi-reviewer consensus patterns for high-confidence code evaluation
177 GitHub stars
Automated iteration loops with configurable limits and exit criteria
Multi-stage user approval gates for cost control and quality validation
Integrated test-driven development (TDD) and user feedback loops

Casos de Uso

Creating automated 'fix-and-verify' loops that iterate until unit tests pass
Structuring user acceptance testing (UAT) with formal approval and feedback cycles
Implementing cost-conscious gates before executing expensive multi-model code reviews

Acerca de

Características Principales

Standardized 4-level issue severity classification (CRITICAL to LOW)
Multi-reviewer consensus patterns for high-confidence code evaluation
177 GitHub stars
Automated iteration loops with configurable limits and exit criteria
Multi-stage user approval gates for cost control and quality validation
Integrated test-driven development (TDD) and user feedback loops

Casos de Uso

Creating automated 'fix-and-verify' loops that iterate until unit tests pass
Structuring user acceptance testing (UAT) with formal approval and feedback cycles
Implementing cost-conscious gates before executing expensive multi-model code reviews