by Weizhena · Claude Skill · ★ 396
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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. Use Cases Academic Research: Paper surveys, benchmark reviews, literature analysis Technical Research: Technology comparison, framework evaluation, tool selection Market Research: Competitor analysis, industry trends, product comparison Due Diligence: Company research, investment analysis, risk assessment Installation Claude Code OpenCode (default: gpt-5.4) bash Skills (same as Claude Code) cp -r skills/research-en/ /.clau
| Stars | 396 |
| Forks | 41 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 54.508/100 |
| Last Updated | 2026-04-10 |
| Created | 2025-12-29 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~452k |
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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 396 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 396 stars and 41 forks, indicating an active community.
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