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Dr. Claw: An AI Scientist Workspace for Vibe Research

Song, Dingjie, Zhang, Hanrong, Liu, Dawei, Liu, Yixin, Li, Zongxia, Yuan, Zhengqing, Zhang, Siqi, Zou, Henry Peng, Yan, Zhiling, Zhang, Yuxuan, Ye, Yanfang, Yu, Philip S., Sun, Lichao

Paper / source record · 2026-08-31

arXiv Project Code

Research question and approach

Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, yet end-to-end research still fragments across chat tools, IDEs, terminals, and writing environments, and the decisions that make it auditable are rarely preserved. We present Dr. Claw, an open-source workspace that wraps existing coding-agent executors in a controllable and auditable human-in-the-loop workflow rather than introducing another autonomous agent.

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Reference this system when discussing integrated research workspaces for coding agents. System availability and workflow capabilities should be checked against the current release.

Author-written abstract

Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, yet end-to-end research still fragments across chat tools, IDEs, terminals, and writing environments, and the decisions that make it auditable are rarely preserved. We present Dr. Claw, an open-source workspace that wraps existing coding-agent executors in a controllable and auditable human-in-the-loop workflow rather than introducing another autonomous agent. Persistent state objects, a reusable skill library, and multi-executor coordination link human decisions to AI execution, turning planning, execution, and writing into one traceable, recoverable loop. We demonstrate Dr. Claw through an interactive three-view scenario and a failure-recovery walkthrough, and evaluate it against a bare command-line agent sharing the same backend executor, so the comparison contrasts the whole orchestration layer (task graph, state objects, and skill library) with the agent it wraps. Holding the executor fixed, Dr. Claw scores higher on research completeness while persisting an auditable, recoverable process trail. Demo access: repository https://github.com/OpenLAIR/dr-claw, released under AGPL-3.0 with GPL-3.0 upstream components.

Abstract source: https://arxiv.org/abs/2609.00365. Checked 2026-09-14. Bibliographic metadata uses the linked paper record or author-maintained catalog. Results, limitations and experimental settings remain defined by the original source.

Citation

BibTeX · CITATION.cff

BibTeX is preserved from the author-maintained citation repository. The CFF uses the source metadata shown on this page. Version titles or author lists can differ; choose the version you used.

@article{song2026dr,
  title={Dr. Claw: An AI Scientist Workspace for Vibe Research},
  author={Song, Dingjie and Zhang, Hanrong and Liu, Dawei and Liu, Yixin and Li, Zongxia and Yuan, Zhengqing and Zhang, Siqi and Zou, Henry Peng and Yan, Zhiling and Zhang, Yuxuan and others},
  journal={arXiv preprint arXiv:2609.00365},
  year={2026}
}