114 lines
3.4 KiB
Markdown
114 lines
3.4 KiB
Markdown
# Deep Research Skill for Claude Code / OpenCode
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[English](README.md) | [中文](README.zh.md)
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> If you find this project helpful, please give it a star! :star:
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> Inspired by [RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context](https://arxiv.org/abs/2511.18743)
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A structured research workflow skill for Claude Code, supporting two-phase research: outline generation (extensible) and deep investigation. Human-in-the-loop design ensures precise control at every stage.
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## Use Cases
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- **Academic Research**: Paper surveys, benchmark reviews, literature analysis
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- **Technical Research**: Technology comparison, framework evaluation, tool selection
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- **Market Research**: Competitor analysis, industry trends, product comparison
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- **Due Diligence**: Company research, investment analysis, risk assessment
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## Installation
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### Claude Code
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```bash
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# English version
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cp -r skills/research-en/* ~/.claude/skills/
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# Chinese version
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cp -r skills/research-zh/* ~/.claude/skills/
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# Required: Install agent and modules
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cp agents/web-search-agent.md ~/.claude/agents/
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cp -r agents/web-search-modules ~/.claude/agents/
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# Required: Install Python dependency
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pip install pyyaml
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```
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### OpenCode (default: gpt-5.2)
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```bash
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# Skills (same as Claude Code)
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cp -r skills/research-en/* ~/.claude/skills/ # or research-zh for Chinese
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# Required: Install agent and modules
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cp agents/web-search-opencode.md ~/.config/opencode/agents/web-search.md
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cp -r agents/web-search-modules ~/.config/opencode/agents/
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# Required: Install Python dependency
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pip install pyyaml
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```
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## Commands
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> **Claude Code 2.1.0+**: Direct `/skill-name` trigger is now supported!
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>
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> **Older versions**: Use `run /skill-name` format instead.
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| Command (2.1.0+) | Description |
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|------------------|-------------|
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| `/research` | Generate research outline with items and fields |
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| `/research-add-items` | Add more research items to existing outline |
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| `/research-add-fields` | Add more field definitions to existing outline |
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| `/research-deep` | Deep research each item with parallel agents |
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| `/research-report` | Generate markdown report from JSON results |
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## Workflow & Example
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> **Example**: Researching "AI Agent Demo 2025"
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### Phase 1: Generate Outline
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```
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/research AI Agent Demo 2025
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```
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💡 **What will happen**: Tell it your topic → It creates a research list for you
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**You get**: A list of 17 AI Agents to research (ChatGPT Agent, Claude Computer Use, Cursor, etc.) + what info to collect for each
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### (Optional) Not satisfied? Add more
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```
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/research-add-items
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/research-add-fields
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```
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💡 **What will happen**: Add more research items or field definitions
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### Phase 2: Deep Research
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```
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/research-deep
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```
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💡 **What will happen**: AI automatically searches the web for each item, one by one
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**You get**: Detailed info for each Agent (company, release date, pricing, tech specs, reviews...)
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### Phase 3: Generate Report
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```
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/research-report
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```
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💡 **What will happen**: All data → One organized report
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**You get**: `report.md` - A complete markdown report with table of contents, ready to read or share
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## Need Help?
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If you have questions, ask Claude Code to explain this project:
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```
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Help me understand this project: https://github.com/Weizhena/deep-research-skills
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```
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## References
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- RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
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## License
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MIT
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