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Found 106 Skills
Execute a single Ralph iteration - implement one user story autonomously. Use for manual mode where you want maximum control and fresh context per story. Triggers on: ralph iterate, execute one story, run single iteration, manual ralph.
Patterns for Ralph loop tasks. Auto-loaded to provide guidance on completion signals, progress tracking, and iteration patterns. Ralph = autonomous issue-to-merged-PR loop.
Use when reporting progress in autonomous loop iterations. Triggers at the end of every autonomous loop iteration, when the autonomous-loop skill completes a BUILD phase, when progress reporting is needed for monitoring or exit evaluation, or when producing machine-parseable RALPH_STATUS blocks with exit signal protocol.
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.
Use this skill whenever a user wants to run, install, configure, or understand open-ralph-wiggum (ralph). This skill can be used by any AI assistant or IDE agent (GitHub Copilot, Claude Code, Cursor, Windsurf, etc.). Triggers on: "ralph", "ralph wiggum", "agentic loop", "iterative AI loop", "autonomous coding loop", "how to install ralph", "how to use ralph with Claude Code / Codex / Copilot / OpenCode", "ralph --agent", "ralph --tasks", "ralph --status", "--max-iterations", "--rotation", "how do I run ralph in VS Code / Cursor / JetBrains / Neovim", or any question about looping an AI coding agent until a task is done. Even if the user doesn't say "ralph" explicitly — if they want to run an AI agent in a loop until a promise tag appears in its output, use this skill.
Self-referential development loop with ultrawork mode - continues until verified task completion
Transforms a rough idea into a detailed design document with implementation plan. Follows Prompt-Driven Development — iterative requirements clarification, research, design, and planning.
Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.
Runs autonomous loop fetching stories from GitHub Issues. Implements and closes issues as done. Triggers on "loop through my PRDs", "work on my issues", "start the autonomous loop", "implement my PRDs", or requests to work through GitHub issues autonomously.
Use this skill when the user asks to "analyze my content", "learn my writing style", "research competitors", "find content angles", "improve my blog", "write like me", "embody my brand voice", or mentions content strategy, voice analysis, competitive research, or iterative content improvement.
Use when automating an iterative GitHub Copilot review loop on a PR — triggers Copilot review, addresses its feedback one comment at a time, and re-triggers up to 2 cycles until all critical issues are resolved.
Autonomous TDD development loop with parallel agent swarm, category evolution, and convergence detection. Use when running autonomous game development, quality improvement loops, or comprehensive codebase reviews.