Loading...
Loading...
Found 26 Skills
Complete setup for automated agent-driven development. Define features as user stories with testable acceptance criteria, then run AI agents in a loop until all stories pass.
Run, monitor, resume, merge, and debug Ralph loops. Use this skill whenever the user asks to operate `ralph run` or `ralph loops`, inspect loop state, recover suspended loops, analyze diagnostics, or unblock merge queue issues.
Create autonomous iterative loops (Ralph Wiggum pattern) for multi-step tasks. Use when setting up automated workflows that iterate over a backlog of tasks with clear acceptance criteria. Triggers on requests like "create a ralph loop", "set up an iterative agent", "automate this migration", or "create an autonomous loop".
Run a coding agent in an autonomous loop via a /ralph command, gated by a preflight check that every CLI is installed, linked, and authenticated. Use when driving long-running autonomous development from a wide, outcome-focused prompt.
Use when performing ralph wiggum style long-running development loops with pacing control.
Generates iterable checklist PROMPT files for Ralph Loop from plan files or current context, and provides the /ralph-loop execution command.
Start a Ralph Loop for iterative self-referential development. Use when the user asks to run a ralph loop, start an iterative loop, or wants repeated autonomous iteration on a task until completion.
Activate autonomous Ralph Wiggum loop mode for iterative task completion. Use when you have a well-defined task with clear completion criteria that benefits from persistent, autonomous execution.
Self-referential completion loop for OpenCode. Re-injects continuation prompts until the task is fully complete with a completion promise.
Ralph Wiggum-inspired automation loop for specification-driven development. Orchestrates task implementation, review, cleanup, and synchronization using a Python script. Use when: user runs /loop command, user asks to automate task implementation, user wants to iterate through spec tasks step-by-step, or user wants to run development workflow automation with context window management. One step per invocation. State machine: init → choose_task → implementation → review → fix → cleanup → sync → update_done. Supports --from-task and --to-task for task range filtering. State persisted in fix_plan.json.
Self-referential development loop with ultrawork mode - continues until verified task completion
Initialize a PRD (Product Requirements Document) for structured ralph-loop execution