by Th0rgal
Type `ralph "prompt"` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot
# Add to your Claude Code skills
git clone https://github.com/Th0rgal/open-ralph-wiggumGuides for using ai agents skills like open-ralph-wiggum.
Last scanned: 4/27/2026
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}open-ralph-wiggum is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Th0rgal. Type `ralph "prompt"` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot. It has 1,841 GitHub stars.
Yes. open-ralph-wiggum passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/Th0rgal/open-ralph-wiggum" and add it to your Claude Code skills directory (see the Installation section above).
open-ralph-wiggum is primarily written in TypeScript. It is open-source under Th0rgal on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh open-ralph-wiggum against similar tools.
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Open Ralph Wiggum works with multiple AI coding agents. Switch between them using the --agent flag:
| Agent | Flag | Description |
|---|---|---|
| Claude Code | --agent claude-code |
Anthropic's Claude Code CLI for autonomous coding |
| Codex | --agent codex |
OpenAI's Codex CLI for AI-powered development |
| Copilot CLI | --agent copilot |
GitHub Copilot CLI for agentic coding |
| Cursor Agent | --agent cursor-agent |
Cursor Agent CLI for headless AI coding |
| Qwen Code | --agent qwen-code |
Alibaba's Qwen Code CLI for headless AI coding |
| OpenCode | --agent opencode |
Default agent, open-source AI coding assistant |
# Use Claude Code
ralph "Build a REST API" --agent claude-code --max-iterations 10
# Use OpenAI Codex
ralph "Create a CLI tool" --agent codex --max-iterations 10
# Use Copilot CLI
ralph "Refactor the auth module" --agent copilot --max-iterations 10
# Use Cursor Agent
ralph "Add unit tests" --agent cursor-agent --max-iterations 10
# Use Qwen Code
ralph "Add unit tests" --agent qwen-code --max-iterations 10
# Use OpenCode (default)
ralph "Fix the failing tests" --max-iterations 10
Open Ralph Wiggum implements the Ralph Wiggum technique — an autonomous agentic loop where an AI coding agent (Claude Code, Codex, Copilot CLI, Cursor Agent, Qwen Code, or OpenCode) receives the same prompt repeatedly until it completes a task. Each iteration, the AI sees its previous work in files and git history, enabling self-correction and incremental progress.
This is a CLI tool that wraps any supported AI coding agent in a persistent development loop. No plugins required — just install and run.
# The essence of the Ralph loop:
while true; do
claude-code "Build feature X. Output <promise>DONE</promise> when complete." # or codex, copilot, cursor-agent, qwen, opencode
done
Why this works: The AI doesn't talk to itself between iterations. It sees the same prompt each time, but the codebase has changed from previous iterations. This creates a powerful feedback loop where the agent iteratively improves its work until all tests pass.
Switch between AI coding agents without changing your workflow:
--agent claude-code) — Anthropic's powerful coding agent--agent codex) — OpenAI's code-specialized model--agent copilot) — GitHub's agentic coding tool--agent cursor-agent) — Cursor's headless AI coding agent--agent qwen-code) — Alibaba's Qwen Code headless CLI agent--agent opencode) — Open-source default option--tasks mode--status from another terminal--add-context without stopping| Benefit | How it works |
|---|---|
| Self-Correction | AI sees test failures from previous runs, fixes them |
| Persistence | Walk away, come back to completed work |
| Iteration | Complex tasks broken into incremental progress |
| Automation | No babysitting—loop handles retries |
| Observability | Monitor progress with --status, see history and struggle indicators |
| Mid-Loop Guidance | Inject hints with --add-context without stopping the loop |
Prerequisites:
npm install -g @th0rgal/ralph-wiggum
bun add -g @th0rgal/ralph-wiggum
git clone https://github.com/Th0rgal/open-ralph-wiggum
cd open-ralph-wiggum
./install.sh
git clone https://github.com/Th0rgal/open-ralph-wiggum
cd open-ralph-wiggum
.\install.ps1
This installs the ralph CLI command globally.
# Simple task with iteration limit
ralph "Create a hello.txt file with 'Hello World'. Output <promise>DONE</promise> when complete." \
--max-iterations 5
# Build something real
ralph "Build a REST API for todos with CRUD operations and tests. \
Run tests after each change. Output <promise>COMPLETE</promise> when all tests pass." \
--max-iterations 20
# Use Claude Code instead of OpenCode
ralph "Create a small CLI and document usage. Output <promise>COMPLETE</promise> when done." \
--agent claude-code --model claude-sonnet-4 --max-iterations 5
# Use Codex instead of OpenCode
ralph "Create a small CLI and document usage. Output <promise>COMPLETE</promise> when done." \
--agent codex --model gpt-5-codex --max-iterations 5
# Use Codex goal mode through OMX: Ralph owns cross-iteration retries, /goal owns one iteration
RALPH_CODEX_GOAL=1 RALPH_CODEX_BACKEND=omx \
ralph "Complete the task described in .harness/goal.md. Output <promise>COMPLETE</promise> when everything passes." \
--agent codex --max-iterations 5
# Use Copilot CLI
ralph "Create a small CLI and document usage. Output <promise>COMPLETE</promise> when done." \
--agent copilot --max-iterations 5
# Use Qwen Code
ralph "Create a small CLI and document usage. Output <promise>COMPLETE</promise> when done." \
--agent qwen-code --max-iterations 5
# Complex project with Tasks Mode
ralph "Build a full-stack web application with user auth and database" \
--tasks --max-iterations 50
Configure agent binaries with these environment variables:
| Variable | Description | Default |
|---|---|---|
RALPH_OPENCODE_BINARY |
Path to OpenCode CLI | "opencode" |
RALPH_CLAUDE_BINARY |
Path to Claude Code CLI | "claude" |
RALPH_CODEX_BINARY |
Path to Codex CLI | "codex" |
RALPH_CODEX_GOAL |
Enable Codex goal mode for --agent codex (1, true, yes, on) |
unset |
RALPH_CODEX_BACKEND |
Goal-mode backend: codex or omx |
detected from configured codex command |
RALPH_CODEX_GOAL_NATIVE |
Force native /goal attempt even when support is not pre-confirmed |
unset |
OMX_RALPH_OMX_BIN |
Path to OMX CLI when RALPH_CODEX_BACKEND=omx |
"omx" |
OMX_RALPH_REASONING |
model_reasoning_effort passed to omx exec in goal mode |
"high" |
RALPH_COPILOT_BINARY |
Path to Copilot CLI | "copilot" |
RALPH_CURSOR_AGENT_BINARY |
Path to Cursor Agent CLI | "cursor-agent" |
RALPH_QWEN_CODE_BINARY |
Path to Qwen Code CLI | "qwen" |
Note for Windows users: Ralph automatically resolves .cmd extensions for npm-installed CLIs. If you encounter "command not found" errors, you can use these environment variables to specify the full path to the executable.
ralph "<prompt>" [options]
Options:
--agent AGENT AI agent to use: opencode (default), claude-code, codex, copilot, cursor-agent, qwen-code
--codex-goal Run Codex iterations in goal mode; final Codex/OMX prompt starts with /goal
--codex-backend BACKEND Backend for --codex-goal: codex or omx (default: detect)
--codex-goal-native Force a native /goal attempt even when backend support is unconfirmed
--min-iterations N Minimum iterations before completion allowed (default: 1)
--max-iterations N St