019 GitHub stars
02User preference alignment scoring to ensure AI decisions match individual coding styles and verbosity.
03Automated risk-benefit analysis to evaluate the technical impact and schedule risks of changes.
04Structured recommendation evaluation using weighted confidence scores and historical success data.
05Multi-criteria decision analysis (MCDA) for weighing competing architectural approaches.
06Eisenhower Matrix integration for prioritizing urgent versus important development tasks.