What problem does it solve?
This Skill removes the heavy lifting of managing an AI-assisted task lifecycle—turning rough ideas into executable implementation plans, running headless agents to make code changes, and producing a clear status/result trail.
Core Features & Use Cases
- Unified lifecycle control: create tasks, triage them into an executable spec, execute via headless agents, and report status.
- Deterministic execution orchestration: launches plans in isolated git worktrees, verifies changes using a fenced verification block, and merges (or leaves for manual review).
- Robust state tracking & recovery: uses a directory-as-state-machine (.todo-tasks/ → .running/ → .done//.archived/) plus an emergency finalizer to avoid stuck runs.
- Chain execution: run multiple triaged plans in sequence using a chain worktree, then merge the chain back into the trunk.
- Operational dashboards: live monitoring and comprehensive status reporting with clear buckets (success, ready, questionable, attention).
Quick Start
Tell your AI to execute the next triaged task by running: "/todo-task execute add-user-search" and then watch progress via the status output.