Audits codebases against the 12 leverage points framework to optimize them for autonomous agentic coding.
Leverage Point Audit is a specialized diagnostic tool designed to evaluate how agent-ready a codebase is by analyzing twelve critical leverage points. By examining factors such as test coverage, logging visibility, architectural clarity, and context documentation, it identifies exactly why AI agents may struggle or fail in a specific environment. This skill provides a structured, prioritized roadmap of improvements, helping development teams bridge the gap between human-centric code and AI-optimized workflows to significantly increase agent success rates and autonomy.
주요 기능
011 GitHub stars
02Identifies critical gaps in testing, logging, and documentation
03Provides prioritized recommendations based on impact and effort
04Automates health checks for agentic capability and success metrics
05Evaluates codebase readiness against the 12 leverage points framework
06Detects anti-patterns like silent failures and information-poor type definitions
사용 사례
01Conducting periodic audits to maintain high AI performance and developer productivity
02Preparing a legacy repository for autonomous maintenance by AI agents
03Troubleshooting recurring failures or low success rates in agentic coding tasks
