What's Your Codebase's Dark Factory Score?
AI tools are only as effective as the codebase they work in. DAF Benchmark scans your GitHub repo and scores it across 5 dimensions of AI readiness -- so you know exactly where to invest before you hand your codebase to an AI agent.
5 Dimensions of AI Readiness
Context Readiness
25% weightCan AI understand your codebase without a human explaining it?
Test Infrastructure
25% weightCan AI validate its own changes?
Architecture Clarity
20% weightCan AI navigate your code and understand component boundaries?
Automation Maturity
15% weightHow much of your workflow runs without human intervention?
AI Integration
15% weightIs AI a first-class development partner in your workflow?
AI Agents Fail in Unprepared Codebases
You can buy the best AI coding tools on the market. But if your repo has no tests, no documentation, no CI pipeline, and a tangled architecture -- the AI will produce garbage as fast as a human would. The bottleneck isn't the AI. It's your codebase's readiness for AI collaboration. DAF Benchmark measures that readiness and tells you exactly what to fix.
Repos Scored This Week
Track AI Readiness Across Your Organization
One repo score is useful. Seeing the trend across 50 repos is transformative. DAF Benchmark Team gives engineering leaders a dashboard showing AI readiness across every repo in the org -- with historical trends, team comparisons, and actionable recommendations.