The tool implements an RLCR (Reinforcement Learning with Code Review) workflow where AI-generated code is continuously refined through feedback loops. It alternates between an implementation phase where Claude works and Codex reviews summaries, and a code review phase where Codex checks quality with severity markers. Issues feed back into implementation until acceptance criteria are met, with optional parallelization via agent teams.