No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Th0rgal · Codex Skill · ★ 1.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is open-ralph-wiggum safe to install? View the security audit →
Open Ralph Wiggum Autonomous Agentic Loop for Claude Code, Codex, Copilot CLI, Cursor Agent & OpenCode Works with Claude Code, OpenAI Codex, Copilot CLI, Cursor Agent, and OpenCode — switch agents with --agent. Based on the Ralph Wiggum technique by Geoffrey Huntley Supported Agents • What is Ralph? • Installation • Quick Start • Commands Tired of agents breaking your local environme
| Stars | 1,892 |
| Forks | 143 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 77.4352485935783/100 |
| Open Issues | 8 |
| Last Updated | 2026-06-02 |
| Created | 2026-01-06 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~1505k |
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open-ralph-wiggum is 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 is categorized as a Codex Skill with 1.9k GitHub stars.
open-ralph-wiggum is primarily written in TypeScript. It covers topics such as claude-code, open-code, opencode.
You can find installation instructions and usage details in the open-ralph-wiggum GitHub repository at github.com/Th0rgal/open-ralph-wiggum. The project has 1.9k stars and 143 forks, indicating an active community.
open-ralph-wiggum is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to open-ralph-wiggum on Agent Skills Hub include ralph-orchestrator, ralphy, awesome-agent-orchestrators. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: