by AgentR1 · Codex Skill · ★ 183
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Claw-R1: The Data Foundation for Agentic Reinforcement Learning News [2026.06] Claw-R1 Demo Technical Report Updated. We updated the Claw-R1 Demo technical report: https://arxiv.org/abs/2606.09138. [2026.06] Claw-R1 Dashboard Released. The live dashboard adds Agentic RL data lifestyle management: collection monitoring, step-level representation, curation signals, prefix-tree optimization preview, and training consumption tracking. [2026.04] 🌲 Prefix Tree Merge for Agentic RL Training. A new algorithm that deduplicates shared prefix computation in multi-step agent training via prefix tree packing + FlexAttention. Currently under testing on the [](https://github.com/AgentR1/Claw-R1/tree/prefix-tree-merge
| Stars | 183 |
| Forks | 9 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.2550818993976/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-05 |
| Created | 2026-03-03 |
| Platforms | python |
| Est. Tokens | ~176k |
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Claw-R1 is Claw-R1: Empowering OpenClaw with Advanced Agentic RL.. It is categorized as a Codex Skill with 183 GitHub stars.
Claw-R1 is primarily written in Python. It covers topics such as agent, agentic-rl, openclaw.
You can find installation instructions and usage details in the Claw-R1 GitHub repository at github.com/AgentR1/Claw-R1. The project has 183 stars and 9 forks, indicating an active community.
Claw-R1 is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Claw-R1 on Agent Skills Hub include n8n-claw, JoySafeter, octocode-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.