jilinchenandClaude Opus 4.5
5dcafa4ef0
- README.md for English (default) - README.zh.md for Chinese - Add language switch links at top 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
80 lines
2.5 KiB
Markdown
80 lines
2.5 KiB
Markdown
# Deep Research Skill for Claude Code
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[English](README.md) | [中文](README.zh.md)
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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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```bash
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# English version
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cp -r skills/research-en ~/.claude/skills/research
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# Required: Install agent
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cp agents/web-search-agent.md ~/.claude/agents/
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```
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## Commands
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> **Note**: Use `run /research` instead of `/research` directly, as slash commands conflict with built-in commands.
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| Command | Description |
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|---------|-------------|
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| `run /research` | Generate research outline with items and fields |
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| `run /research/add-items` | Add more items to existing outline |
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| `run /research/add-fields` | Add more fields to existing outline |
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| `run /research/deep` | Deep research each item with parallel agents |
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| `run /research/report` | Generate markdown report from JSON results |
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## Workflow
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### Phase 1: Generate Outline
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```
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run /research <topic>
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```
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- Model knowledge generates initial items and field framework
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- Web search supplements latest items
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- User confirms and adjusts
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- Outputs: `outline.yaml` (items + config) + `fields.yaml` (field definitions)
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### Phase 2: Deep Research
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```
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run /research/deep
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```
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- Parallel agents research each item (batch_size configurable)
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- Each agent reads fields.yaml and outputs structured JSON
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- Supports checkpoint resume
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- Outputs: `results/*.json`
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### Optional: Expand Outline
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```
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run /research/add-items # Add research targets via user input or web search
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run /research/add-fields # Add field definitions
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```
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### Phase 3: Generate Report
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```
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run /research/report
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```
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- Generates Python script to convert JSON to markdown
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- User selects summary fields for TOC
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- Skips uncertain values automatically
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- Outputs: `report.md`
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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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