Enforces rigorous code quality standards and security audits for AI-generated code through the Big 5 methodology.
The Quality skill addresses the increased bug density in AI-generated code by implementing the 'Big 5' validation framework: input validation, edge cases, error handling, duplication, and complexity checks. Beyond simple linting, it introduces the R-factor—a sophisticated composite score that evaluates code based on test pass rates, security, and scope accuracy. By integrating proactive deviation detection (ADSR), this skill monitors for behavioral anomalies like scope creep or unusual token usage, ensuring that AI-assisted development remains high-quality, secure, and production-ready.
Características Principales
01Automated Security Audits: Scans for SQL injection, missing schema validations, and unsafe catch blocks using Grep and Bash.
02Enforced Verdicts: Implements a strict 'Fix before commit' policy for any Big 5 violations.
03Proactive Deviation Detection (ADSR): Identifies and alerts on behavioral anomalies like token spikes or scope creep.
04Big 5 Validation: Automates checks for input validation, edge cases, error handling, duplication, and complexity.
05R-factor Scoring: Generates a composite quality metric (0.0 to 1.0) to determine production readiness.
069 GitHub stars
Casos de Uso
01Hardening AI-generated code before merging into production branches.
02Tracking code quality improvements over time using historical R-factor metrics.
03Automating code reviews to identify technical debt and security vulnerabilities.
