What problem does it solve? AI coding sessions often stall mid-task, requiring repeated manual "keep going" prompts and offering no clear signal of when work is actually done. This Skill runs tasks autonomously through structured iterations with explicit completion criteria, so multi-step work finishes without constant supervision. ## Core Features & Use Cases - Dual-Condition Exit Gate: Loops exit only when at least two completion indicators (commits, passing tests, docs, markers) are met AND an explicit EXIT_SIGNAL is emitted, preventing premature or runaway termination. - Stagnation Detection with Auto-Diversification: State hashing detects repeated no-progress iterations; in autonomous mode it applies combine, radical, or reread recovery strategies instead of pausing for user input. - Phase Tracking and Status Blocks: Auto-detects INIT, RESEARCH, IMPL, VERIFY, and COMPLETE phases and renders a NAVIGATOR_STATUS block with progress percentage and machine-readable pilot-signal JSON each iteration. - Use Case: Tell the agent "Run until done: add user authentication with tests" and it iterates through research, implementation, and verification, committing changes and emitting a completion signal only when tests pass and criteria are met. ## Quick Start Ask the agent to run until done implementing your feature, for example: "Run until done: add an isPrime function with passing tests."