{"id":41672092,"url":"https://github.com/Th0rgal/open-ralph-wiggum","last_synced_at":"2026-02-03T11:05:06.366Z","repository":{"id":331701039,"uuid":"1128833454","full_name":"Th0rgal/open-ralph-wiggum","owner":"Th0rgal","description":"Type `ralph \"prompt\"` to start open code in a ralph loop. Also supports a prompt file \u0026 status check. Open Code, Claude Code, Codex","archived":false,"fork":false,"pushed_at":"2026-02-02T13:33:54.000Z","size":22018,"stargazers_count":784,"open_issues_count":10,"forks_count":65,"subscribers_count":13,"default_branch":"master","last_synced_at":"2026-02-03T02:44:10.067Z","etag":null,"topics":["claude-code","open-code","opencode","ralph","ralph-wiggum"],"latest_commit_sha":null,"homepage":"","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Th0rgal.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-01-06T08:06:47.000Z","updated_at":"2026-02-02T23:22:30.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/Th0rgal/open-ralph-wiggum","commit_stats":null,"previous_names":["th0rgal/opencode-ralph-wiggum","th0rgal/open-ralph-wiggum"],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/Th0rgal/open-ralph-wiggum","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Th0rgal%2Fopen-ralph-wiggum","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Th0rgal%2Fopen-ralph-wiggum/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Th0rgal%2Fopen-ralph-wiggum/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Th0rgal%2Fopen-ralph-wiggum/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Th0rgal","download_url":"https://codeload.github.com/Th0rgal/open-ralph-wiggum/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Th0rgal%2Fopen-ralph-wiggum/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29043778,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-03T10:09:22.136Z","status":"ssl_error","status_checked_at":"2026-02-03T10:09:16.814Z","response_time":96,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["claude-code","open-code","opencode","ralph","ralph-wiggum"],"created_at":"2026-01-24T18:01:50.556Z","updated_at":"2026-02-03T11:05:05.736Z","avatar_url":"https://github.com/Th0rgal.png","language":"TypeScript","funding_links":[],"categories":["Implementations"],"sub_categories":["Tool-Specific Implementations"],"readme":"\u003cp align=\"center\"\u003e\n  \u003ch1 align=\"center\"\u003eOpen Ralph Wiggum\u003c/h1\u003e\n  \u003ch3 align=\"center\"\u003eAutonomous Agentic Loop for Claude Code, Codex \u0026 OpenCode\u003c/h3\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"screenshot.webp\" alt=\"Open Ralph Wiggum - Iterative AI coding loop for Claude Code and Codex\" /\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cstrong\u003eRun any AI coding agent in a self-correcting loop until your task is done.\u003c/strong\u003e\u003cbr\u003e\n  \u003cem\u003eWorks with \u003cb\u003eClaude Code\u003c/b\u003e, \u003cb\u003eOpenAI Codex\u003c/b\u003e, and \u003cb\u003eOpenCode\u003c/b\u003e — switch agents with \u003ccode\u003e--agent\u003c/code\u003e.\u003c/em\u003e\u003cbr\u003e\n  \u003cem\u003eBased on the \u003ca href=\"https://ghuntley.com/ralph/\"\u003eRalph Wiggum technique\u003c/a\u003e by Geoffrey Huntley\u003c/em\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/Th0rgal/ralph-wiggum/blob/master/LICENSE\"\u003e\u003cimg src=\"https://img.shields.io/badge/license-MIT-blue.svg\" alt=\"MIT License\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://github.com/Th0rgal/ralph-wiggum\"\u003e\u003cimg src=\"https://img.shields.io/badge/built%20with-Bun%20%2B%20TypeScript-f472b6.svg\" alt=\"Built with Bun + TypeScript\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://github.com/Th0rgal/ralph-wiggum/releases\"\u003e\u003cimg src=\"https://img.shields.io/github/v/release/Th0rgal/ralph-wiggum?include_prereleases\" alt=\"Release\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"#supported-agents\"\u003eSupported Agents\u003c/a\u003e •\n  \u003ca href=\"#what-is-open-ralph-wiggum\"\u003eWhat is Ralph?\u003c/a\u003e •\n  \u003ca href=\"#installation\"\u003eInstallation\u003c/a\u003e •\n  \u003ca href=\"#quick-start\"\u003eQuick Start\u003c/a\u003e •\n  \u003ca href=\"#commands\"\u003eCommands\u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cstrong\u003eTired of agents breaking your local environment?\u003c/strong\u003e\u003cbr\u003e\n  \u003ca href=\"https://github.com/Th0rgal/openagent\"\u003eOpenAgent\u003c/a\u003e gives each task an isolated Linux workspace. Self-hosted. Git-backed.\n\u003c/p\u003e\n\n---\n\n## Supported Agents\n\nOpen Ralph Wiggum works with multiple AI coding agents. Switch between them using the `--agent` flag:\n\n| Agent | Flag | Description |\n|-------|------|-------------|\n| **Claude Code** | `--agent claude-code` | Anthropic's Claude Code CLI for autonomous coding |\n| **Codex** | `--agent codex` | OpenAI's Codex CLI for AI-powered development |\n| **OpenCode** | `--agent opencode` | Default agent, open-source AI coding assistant |\n\n```bash\n# Use Claude Code\nralph \"Build a REST API\" --agent claude-code --max-iterations 10\n\n# Use OpenAI Codex\nralph \"Create a CLI tool\" --agent codex --max-iterations 10\n\n# Use OpenCode (default)\nralph \"Fix the failing tests\" --max-iterations 10\n```\n\n---\n\n## What is Open Ralph Wiggum?\n\nOpen Ralph Wiggum implements the **Ralph Wiggum technique** — an autonomous agentic loop where an AI coding agent (Claude Code, Codex, 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.\n\nThis is a **CLI tool** that wraps any supported AI coding agent in a persistent development loop. No plugins required — just install and run.\n\n```bash\n# The essence of the Ralph loop:\nwhile true; do\n  claude-code \"Build feature X. Output \u003cpromise\u003eDONE\u003c/promise\u003e when complete.\"  # or codex, opencode\ndone\n```\n\n**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.\n\n### Multi-Agent Flexibility\n\nSwitch between AI coding agents without changing your workflow:\n\n- **Claude Code** (`--agent claude-code`) — Anthropic's powerful coding agent\n- **Codex** (`--agent codex`) — OpenAI's code-specialized model\n- **OpenCode** (`--agent opencode`) — Open-source default option\n\n## Key Features\n\n- **Multi-Agent Support** — Use Claude Code, Codex, or OpenCode with the same workflow\n- **Self-Correcting Loops** — Agent sees its previous work and fixes its own mistakes\n- **Autonomous Execution** — Set it running and come back to finished code\n- **Task Tracking** — Built-in task management with `--tasks` mode\n- **Live Monitoring** — Check progress with `--status` from another terminal\n- **Mid-Loop Hints** — Inject guidance with `--add-context` without stopping\n\n## Why Use an Agentic Loop?\n\n| Benefit | How it works |\n|---------|--------------|\n| **Self-Correction** | AI sees test failures from previous runs, fixes them |\n| **Persistence** | Walk away, come back to completed work |\n| **Iteration** | Complex tasks broken into incremental progress |\n| **Automation** | No babysitting—loop handles retries |\n| **Observability** | Monitor progress with `--status`, see history and struggle indicators |\n| **Mid-Loop Guidance** | Inject hints with `--add-context` without stopping the loop |\n\n## Installation\n\n**Prerequisites:**\n- [Bun](https://bun.sh) runtime\n- At least one AI coding agent CLI:\n  - [Claude Code](https://docs.anthropic.com/en/docs/claude-code) — Anthropic's Claude Code CLI\n  - [Codex](https://github.com/openai/codex) — OpenAI's Codex CLI\n  - [OpenCode](https://opencode.ai) — Open-source AI coding assistant\n\n### npm (recommended)\n\n```bash\nnpm install -g @th0rgal/ralph-wiggum\n```\n\n### Bun\n\n```bash\nbun add -g @th0rgal/ralph-wiggum\n```\n\n### From source\n\n```bash\ngit clone https://github.com/Th0rgal/open-ralph-wiggum\ncd open-ralph-wiggum\n./install.sh\n```\n\n```powershell\ngit clone https://github.com/Th0rgal/open-ralph-wiggum\ncd open-ralph-wiggum\n.\\install.ps1\n```\n\nThis installs the `ralph` CLI command globally.\n\n## Quick Start\n\n```bash\n# Simple task with iteration limit\nralph \"Create a hello.txt file with 'Hello World'. Output \u003cpromise\u003eDONE\u003c/promise\u003e when complete.\" \\\n  --max-iterations 5\n\n# Build something real\nralph \"Build a REST API for todos with CRUD operations and tests. \\\n  Run tests after each change. Output \u003cpromise\u003eCOMPLETE\u003c/promise\u003e when all tests pass.\" \\\n  --max-iterations 20\n\n# Use Claude Code instead of OpenCode\nralph \"Create a small CLI and document usage. Output \u003cpromise\u003eCOMPLETE\u003c/promise\u003e when done.\" \\\n  --agent claude-code --model claude-sonnet-4 --max-iterations 5\n\n# Use Codex instead of OpenCode\nralph \"Create a small CLI and document usage. Output \u003cpromise\u003eCOMPLETE\u003c/promise\u003e when done.\" \\\n  --agent codex --model gpt-5-codex --max-iterations 5\n\n# Complex project with Tasks Mode\nralph \"Build a full-stack web application with user auth and database\" \\\n  --tasks --max-iterations 50\n```\n\n## Commands\n\n### Running a Loop\n\n```bash\nralph \"\u003cprompt\u003e\" [options]\n\nOptions:\n  --agent AGENT            AI agent to use: opencode (default), claude-code, codex\n  --min-iterations N       Minimum iterations before completion allowed (default: 1)\n  --max-iterations N       Stop after N iterations (default: unlimited)\n  --completion-promise T   Text that signals completion (default: COMPLETE)\n  --tasks, -t              Enable Tasks Mode for structured task tracking\n  --task-promise T         Text that signals task completion (default: READY_FOR_NEXT_TASK)\n  --model MODEL            Model to use (agent-specific)\n  --prompt-file, --file, -f  Read prompt content from a file\n  --no-stream              Buffer agent output and print at the end\n  --verbose-tools          Print every tool line (disable compact tool summary)\n  --no-plugins             Disable non-auth OpenCode plugins for this run (opencode only)\n  --no-commit              Don't auto-commit after iterations\n  --allow-all              Auto-approve all tool permissions (default: on)\n  --no-allow-all           Require interactive permission prompts\n  --help                   Show help\n```\n\n### Tasks Mode\n\nTasks Mode allows you to break complex projects into smaller, manageable tasks. Ralph works on one task at a time and tracks progress in a markdown file.\n\n```bash\n# Enable Tasks Mode\nralph \"Build a complete web application\" --tasks --max-iterations 20\n\n# Custom task completion signal\nralph \"Multi-feature project\" --tasks --task-promise \"TASK_DONE\"\n```\n\n#### Task Management Commands\n\n```bash\n# List current tasks\nralph --list-tasks\n\n# Add a new task\nralph --add-task \"Implement user authentication\"\n\n# Remove task by index\nralph --remove-task 3\n\n# Show status (tasks shown automatically when tasks mode is active)\nralph --status\n```\n\n#### How Tasks Mode Works\n\n1. **Task File**: Tasks are stored in `.ralph/ralph-tasks.md`\n2. **One Task Per Iteration**: Ralph focuses on a single task to reduce confusion\n3. **Automatic Progression**: When a task completes (`\u003cpromise\u003eREADY_FOR_NEXT_TASK\u003c/promise\u003e`), Ralph moves to the next\n4. **Persistent State**: Tasks survive loop restarts\n5. **Focused Context**: Smaller contexts per iteration reduce costs and improve reliability\n\nTask status indicators:\n- `[ ]` - Not started\n- `[/]` - In progress\n- `[x]` - Complete\n\nExample task file:\n```markdown\n# Ralph Tasks\n\n- [ ] Set up project structure\n- [x] Initialize git repository\n- [/] Implement user authentication\n  - [ ] Create login page\n  - [ ] Add JWT handling\n- [ ] Build dashboard UI\n```\n\n### Monitoring \u0026 Control\n\n```bash\n# Check status of active loop (run from another terminal)\nralph --status\n\n# Add context/hints for the next iteration\nralph --add-context \"Focus on fixing the auth module first\"\n\n# Clear pending context\nralph --clear-context\n```\n\n### Status Dashboard\n\nThe `--status` command shows:\n- **Active loop info**: Current iteration, elapsed time, prompt\n- **Pending context**: Any hints queued for next iteration\n- **Current tasks**: Automatically shown when tasks mode is active (or use `--tasks`)\n- **Iteration history**: Last 5 iterations with tools used, duration\n- **Struggle indicators**: Warnings if agent is stuck (no progress, repeated errors)\n\n```\n╔══════════════════════════════════════════════════════════════════╗\n║                    Ralph Wiggum Status                           ║\n╚══════════════════════════════════════════════════════════════════╝\n\n🔄 ACTIVE LOOP\n   Iteration:    3 / 10\n   Elapsed:      5m 23s\n   Promise:      COMPLETE\n   Prompt:       Build a REST API...\n\n📊 HISTORY (3 iterations)\n   Total time:   5m 23s\n\n   Recent iterations:\n   🔄 #1: 2m 10s | Bash:5 Write:3 Read:2\n   🔄 #2: 1m 45s | Edit:4 Bash:3 Read:2\n   🔄 #3: 1m 28s | Bash:2 Edit:1\n\n⚠️  STRUGGLE INDICATORS:\n   - No file changes in 3 iterations\n   💡 Consider using: ralph --add-context \"your hint here\"\n```\n\n### Mid-Loop Context Injection\n\nGuide a struggling agent without stopping the loop:\n\n```bash\n# In another terminal while loop is running\nralph --add-context \"The bug is in utils/parser.ts line 42\"\nralph --add-context \"Try using the singleton pattern for config\"\n```\n\nContext is automatically consumed after one iteration.\n\n## Troubleshooting\n\n### Plugin errors\n\nThis package is **CLI-only**. If OpenCode tries to load a `ralph-wiggum` or `open-ralph-wiggum` plugin,\nremove it from your OpenCode `plugin` list (opencode.json), or run:\n\n```bash\nralph \"Your task\" --no-plugins\n```\n\n### \"bun: command not found\"\n\nInstall Bun: https://bun.sh\n\n## Writing Good Prompts\n\n### Include Clear Success Criteria\n\n❌ Bad:\n```\nBuild a todo API\n```\n\n✅ Good:\n```\nBuild a REST API for todos with:\n- CRUD endpoints (GET, POST, PUT, DELETE)\n- Input validation\n- Tests for each endpoint\n\nRun tests after changes. Output \u003cpromise\u003eCOMPLETE\u003c/promise\u003e when all tests pass.\n```\n\n### Use Verifiable Conditions\n\n❌ Bad:\n```\nMake the code better\n```\n\n✅ Good:\n```\nRefactor auth.ts to:\n1. Extract validation into separate functions\n2. Add error handling for network failures\n3. Ensure all existing tests still pass\n\nOutput \u003cpromise\u003eDONE\u003c/promise\u003e when refactored and tests pass.\n```\n\n### Always Set Max Iterations\n\n```bash\n# Safety net for runaway loops\nralph \"Your task\" --max-iterations 20\n```\n\n## Recommended PRD Format\n\nRalph treats prompt files as plain text, so any format works. For best results, use a concise PRD with:\n\n- **Goal**: one sentence summary of the desired outcome\n- **Scope**: what is in/out\n- **Requirements**: numbered, testable items\n- **Constraints**: tech stack, performance, security, compatibility\n- **Acceptance criteria**: explicit success checks\n- **Completion promise**: include `\u003cpromise\u003eCOMPLETE\u003c/promise\u003e` (or match your `--completion-promise`)\n\nExample (Markdown):\n\n```markdown\n# PRD: Add Export Button\n\n## Goal\nLet users export reports as CSV from the dashboard.\n\n## Scope\n- In: export current report view\n- Out: background exports, scheduling\n\n## Requirements\n1. Add \"Export CSV\" button to dashboard header.\n2. CSV includes columns: date, revenue, sessions.\n3. Works for reports up to 10k rows.\n\n## Constraints\n- Keep current UI styling.\n- Use existing CSV utility in utils/csv.ts.\n\n## Acceptance Criteria\n- Clicking button downloads a valid CSV.\n- CSV opens cleanly in Excel/Sheets.\n- All existing tests pass.\n\n## Completion Promise\n\u003cpromise\u003eCOMPLETE\u003c/promise\u003e\n```\n\n### JSON Feature List (Recommended for Complex Projects)\n\nFor larger projects, a structured JSON feature list works better than prose. Based on [Anthropic's research on effective agent harnesses](https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents), JSON format reduces the chance of agents inappropriately modifying test definitions.\n\nCreate a `features.json` file:\n\n```json\n{\n  \"features\": [\n    {\n      \"category\": \"functional\",\n      \"description\": \"Export button downloads CSV with current report data\",\n      \"steps\": [\n        \"Navigate to dashboard\",\n        \"Click 'Export CSV' button\",\n        \"Verify CSV file downloads\",\n        \"Open CSV and verify columns: date, revenue, sessions\",\n        \"Verify data matches displayed report\"\n      ],\n      \"passes\": false\n    },\n    {\n      \"category\": \"functional\",\n      \"description\": \"Export handles large reports up to 10k rows\",\n      \"steps\": [\n        \"Load report with 10,000 rows\",\n        \"Click 'Export CSV' button\",\n        \"Verify export completes without timeout\",\n        \"Verify all rows present in CSV\"\n      ],\n      \"passes\": false\n    },\n    {\n      \"category\": \"ui\",\n      \"description\": \"Export button matches existing dashboard styling\",\n      \"steps\": [\n        \"Navigate to dashboard\",\n        \"Verify button uses existing button component\",\n        \"Verify button placement in header area\"\n      ],\n      \"passes\": false\n    }\n  ]\n}\n```\n\nThen reference it in your prompt:\n\n```\nRead features.json for the feature list. Work through each feature one at a time.\nAfter verifying a feature works end-to-end, update its \"passes\" field to true.\nDo NOT modify the description or steps - only change the passes boolean.\nOutput \u003cpromise\u003eCOMPLETE\u003c/promise\u003e when all features pass.\n```\n\n**Why JSON?** Agents are less likely to inappropriately modify JSON test definitions compared to Markdown. The structured format keeps agents focused on implementation rather than redefining success criteria.\n\n## When to Use Ralph\n\n**Good for:**\n- Tasks with automatic verification (tests, linters, type checking)\n- Well-defined tasks with clear completion criteria\n- Greenfield projects where you can walk away\n- Iterative refinement (getting tests to pass)\n\n**Not good for:**\n- Tasks requiring human judgment\n- One-shot operations\n- Unclear success criteria\n- Production debugging\n\n## How It Works\n\n```\n┌─────────────────────────────────────────────────────────────┐\n│                                                             │\n│   ┌──────────┐    same prompt    ┌──────────┐              │\n│   │          │ ───────────────▶  │          │              │\n│   │  ralph   │                   │ AI Agent │              │\n│   │   CLI    │ ◀─────────────── │          │              │\n│   │          │   output + files  │          │              │\n│   └──────────┘                   └──────────┘              │\n│        │                              │                     │\n│        │ check for                    │ modify              │\n│        │ \u003cpromise\u003e                    │ files               │\n│        ▼                              ▼                     │\n│   ┌──────────┐                   ┌──────────┐              │\n│   │ Complete │                   │   Git    │              │\n│   │   or     │                   │  Repo    │              │\n│   │  Retry   │                   │ (state)  │              │\n│   └──────────┘                   └──────────┘              │\n│                                                             │\n└─────────────────────────────────────────────────────────────┘\n```\n\n1. Ralph sends your prompt to the selected agent\n2. The agent works on the task, modifies files\n3. Ralph checks output for completion promise\n4. If not found, repeat with same prompt\n5. AI sees previous work in files\n6. Loop until success or max iterations\n\n## Project Structure\n\n```\nralph-wiggum/\n├── bin/ralph.js                  # CLI entrypoint (npm wrapper)\n├── ralph.ts                      # Main loop implementation\n├── package.json                  # Package config\n├── install.sh / install.ps1     # Installation scripts\n└── uninstall.sh / uninstall.ps1 # Uninstallation scripts\n```\n\n### State Files (in .ralph/)\n\nDuring operation, Ralph stores state in `.ralph/`:\n- `ralph-loop.state.json` - Active loop state\n- `ralph-history.json` - Iteration history and metrics\n- `ralph-context.md` - Pending context for next iteration\n- `ralph-tasks.md` - Task list for Tasks Mode (created when `--tasks` is used)\n\n## Uninstall\n\n```bash\nnpm uninstall -g @th0rgal/ralph-wiggum\n```\n\n```powershell\nnpm uninstall -g @th0rgal/ralph-wiggum\n```\n\n## Agent-Specific Notes\n\n### Claude Code\n\n[Claude Code](https://docs.anthropic.com/en/docs/claude-code) is Anthropic's official CLI for Claude. Use it with Open Ralph Wiggum for powerful autonomous coding:\n\n```bash\nralph \"Refactor the auth module and ensure tests pass\" \\\n  --agent claude-code \\\n  --model claude-sonnet-4 \\\n  --max-iterations 15\n```\n\n### OpenAI Codex\n\n[Codex](https://github.com/openai/codex) is OpenAI's code-specialized agent. Perfect for code generation and refactoring tasks:\n\n```bash\nralph \"Generate unit tests for all utility functions\" \\\n  --agent codex \\\n  --model gpt-5-codex \\\n  --max-iterations 10\n```\n\n### OpenCode\n\n[OpenCode](https://opencode.ai) is an open-source AI coding assistant. It's the default agent:\n\n```bash\nralph \"Fix all TypeScript errors\" --max-iterations 10\n```\n\n## Learn More\n\n- [Original Ralph Wiggum technique by Geoffrey Huntley](https://ghuntley.com/ralph/)\n- [Ralph Orchestrator](https://github.com/mikeyobrien/ralph-orchestrator)\n\n## See Also\n\nCheck out [OpenAgent](https://github.com/Th0rgal/openagent) — a dashboard for orchestrating AI agents with workspace management, real-time monitoring, and multi-agent workflows.\n\n## License\n\nMIT\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FTh0rgal%2Fopen-ralph-wiggum","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FTh0rgal%2Fopen-ralph-wiggum","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FTh0rgal%2Fopen-ralph-wiggum/lists"}