by Weizhena · Claude Skill · ★ 640
Deep Research Skill for Claude Code / OpenCode / Codex English | 中文 If you find this project helpful, please give it a star! :star: Inspired by RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context A structured research workflow skill for Claude Code, OpenCode, and Codex, supporting two-phase research: outline generation (extensible) and deep investigation. Human-in-the-loop design ensures precise control at every stage.
| Stars | 640 |
| Forks | 60 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 56.158/100 |
| Last Updated | 2026-05-07 |
| Created | 2025-12-29 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~452k |
These tools work well together with Deep-Research-skills for enhanced workflows:
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Deep-Research-skills is Structured deep research skill for Claude Code/Open Code/Codex with human-in-the-loop control. It is categorized as a Claude Skill with 640 GitHub stars.
Deep-Research-skills is primarily written in Python. It covers topics such as claude-code, claude-code-skills, deep-research-agent.
You can find installation instructions and usage details in the Deep-Research-skills GitHub repository at github.com/Weizhena/Deep-Research-skills. The project has 640 stars and 60 forks, indicating an active community.
Deep-Research-skills is released under the MIT license, making it free to use and modify according to the license terms.