What problem does it solve? It prevents context rot and requirement drift in AI-assisted development by storing requirements, plans, and analysis in versioned repo files instead of chat context, enforcing strict phase gates so no step is skipped. ## Core Features & Use Cases - Stage-Gated RLM Workflow: Runs Phases 0-7 (worktree setup, requirements, AS-IS analysis, root cause debugging, planning, TDD implementation, code review, testing, manual QA, global state updates) with SHA-256 lock hashes and hard gates blocking progression until prior phases pass. - TDD and Debugging Discipline: Enforces RED-GREEN-REFACTOR cycles with a mandatory TDD Compliance Log and an optional Phase 1.5 systematic root cause analysis for bug fixes. - Parallel or Sequential Execution: Automatically detects subagent capability to run implementation and test suites concurrently, with a rigorous sequential fallback mode. - Use Case: A developer types "Implement requirement 'add-oauth'" and the workflow auto-resumes through analysis, planning, TDD implementation, and testing in an isolated git worktree, pausing only for manual QA sign-off before updating DECISIONS.md and STATE.md. ## Quick Start Ask the agent to implement requirement '<run-id>' after creating a requirements file at .codex/rlm/<run-id>/00-requirements.md.