by mvschwarz · Codex Skill · ★ 50
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OpenRig A harness wraps a model. A rig wraps your harnesses. Define your agent team in YAML, boot it with one command. Claude Code and Codex in the same rig, managed as one system. OpenRig turns AI coding agents from a pile of terminal sessions into a persistent, organized team. A rig is the team that doesn't go away. If you've got tabs full of agents you're afraid to close, this is the layer you're missing: it's open source, it's local, and you're four commands away. It runs locally: a daemon, a SQLite database, a CLI, and a dashboard. The agents are ordinary Claude Code and Codex sessions in tmux. is the fuller starter, 7 seats, 4 Claude and 3 Codex, with an orchestration HA pair plus development and review pods. Because 4 Claude seats run at once, single-plan users should expect provider throttling. For the light-footprint path, use , a 4-seat starter with 2 Claude and 2 Codex. First Run After boots, shows the running pods and seats. When you're ready to shut the team down and bring it back, use the same rig name: is a fleet glance. sna
| Stars | 50 |
| Forks | 8 |
| Language | TypeScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 68.4339730645156/100 |
| Open Issues | 7 |
| Last Updated | 2026-07-01 |
| Created | 2026-04-01 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~15k |
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openrig is Multi-agent harness that runs Claude Code and Codex together as one system. It is categorized as a Codex Skill with 50 GitHub stars.
openrig is primarily written in TypeScript. It covers topics such as agent-harness, agent-orchestration, agent-skills.
You can find installation instructions and usage details in the openrig GitHub repository at github.com/mvschwarz/openrig. The project has 50 stars and 8 forks, indicating an active community.
openrig is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to openrig on Agent Skills Hub include maestro, claude-code-open, sudocode. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.