What problem does it solve? AI agents often stall by bouncing decisions back to the user with clarifying questions, breaking flow on tasks the user wants done hands-off. This Skill replaces question-asking with evidence-based decision-making so work proceeds to a verifiable end state without interruption. ## Core Features & Use Cases - Two activation modes: FULL mode for session-wide hands-off execution ("yolo", "just do it", the --yolo flag) and DECISION mode for resolving a single delegated fork ("your call", "you decide"). - Resolve-don't-ask protocol: Classifies ambiguity as intent, approach, or fact, then answers it by reading code, running commands, checking git history, or searching the web instead of asking. - Multi-agent fan-out: Spawns parallel sub-agents (explorers, researchers, skeptics) for tasks with real breadth, then reconciles their outputs. - Safety floor: Still stops for confirmation on irreversible, outward-facing, or money-spending actions like force-pushes, unrequested PRs, or external messages. - Use Case: A user says "fix the flaky login test, yolo" — the agent investigates the failure, picks the most defensible fix, verifies it by running the test suite, and reports assumptions made, all without a single question. ## Quick Start Tell the agent "yolo, refactor the auth module and make the tests pass" to have it work autonomously to a verified end state.