What happens if a piece of code scores below 90?

The skill provides actionable feedback specifying exactly what needs to be fixed, where, and why, requiring an iteration before the code is considered production-ready.

How does LLM-as-judge improve code quality?

It uses an independent AI agent to evaluate the implementation with fresh perspective, identifying logical flaws and architectural issues that automated tests might miss.

What is the 5-layer verification pyramid?

It is a structured QA hierarchy that moves from high-automation/low-cost checks (Linting/Types) to low-automation/high-value evaluations (LLM-as-judge Quality Scoring).

Can I use this for security audits?

Yes, Layer 1 includes automated security scanning (SAST) to detect vulnerabilities like SQL injection, XSS, and hardcoded secrets.

Multi-AI Verification Pyramid

Name: Multi-AI Verification Pyramid
Author: adaptationio

byadaptationio

보안 및 테스팅

Validates code quality through a comprehensive 5-layer pyramid using independent LLM-as-judge evaluation for production readiness.

소개

Multi-AI Verification provides a rigorous quality assurance framework designed to ensure code is production-ready. It utilizes a structured 5-layer pyramid—Rules-Based, Functional, Visual, Integration, and Quality Scoring—to identify issues ranging from simple syntax errors to complex logic flaws. By implementing an independent LLM-as-judge pattern, the skill eliminates developer bias and prevents 'test gaming,' providing an objective 0-100 quality score. This progressive validation approach ensures that only code meeting a strict threshold (≥90) reaches deployment, making it an essential tool for high-stakes software engineering.

주요 기능

Independent LLM-as-judge and Agent-as-a-Judge validation patterns
Comprehensive security scanning (SAST) and accessibility auditing
5-Layer Verification Pyramid (Rules → Functional → Visual → Integration → Quality Scoring)
Objective 0-100 quality scoring with customizable pass/fail thresholds
Automated feedback loop providing actionable What/Where/Why/How reports
0 GitHub stars

사용 사례

Automated end-to-end verification of new features including UI and API layers
Preventing test gaming and bias through independent multi-layer validation
Final quality gate and security audit before merging critical PRs into production

소개

주요 기능

Independent LLM-as-judge and Agent-as-a-Judge validation patterns
Comprehensive security scanning (SAST) and accessibility auditing
5-Layer Verification Pyramid (Rules → Functional → Visual → Integration → Quality Scoring)
Objective 0-100 quality scoring with customizable pass/fail thresholds
Automated feedback loop providing actionable What/Where/Why/How reports
0 GitHub stars

사용 사례

Automated end-to-end verification of new features including UI and API layers
Preventing test gaming and bias through independent multi-layer validation
Final quality gate and security audit before merging critical PRs into production