jilinchenandClaude Opus 4.5
39abbd0be3
- Add detailed explanations for each workflow phase - Describe outputs for each stage 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
164 lines
4.4 KiB
Markdown
164 lines
4.4 KiB
Markdown
# Deep Research Skill for Claude Code
|
||
|
||
[English](#english) | [中文](#中文)
|
||
|
||
---
|
||
|
||
## English
|
||
|
||
> Inspired by [RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context](https://arxiv.org/abs/2511.18743)
|
||
|
||
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.
|
||
|
||
### 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
|
||
|
||
### Commands
|
||
|
||
| Command | Description |
|
||
|---------|-------------|
|
||
| `/research` | Generate research outline with items and fields |
|
||
| `/research/add-items` | Add more items to existing outline |
|
||
| `/research/add-fields` | Add more fields to existing outline |
|
||
| `/research/deep` | Deep research each item with parallel agents |
|
||
| `/research/report` | Generate markdown report from JSON results |
|
||
|
||
### Installation
|
||
|
||
Choose your language version:
|
||
|
||
```bash
|
||
# English version
|
||
cp -r skills/research-en ~/.claude/skills/research
|
||
|
||
# Chinese version
|
||
cp -r skills/research-zh ~/.claude/commands/research
|
||
|
||
# Required: Install agent
|
||
cp agents/web-search-agent.md ~/.claude/agents/
|
||
```
|
||
|
||
### Workflow
|
||
|
||
#### Phase 1: Generate Outline
|
||
```
|
||
/research <topic>
|
||
```
|
||
- Model knowledge generates initial items and field framework
|
||
- Web search supplements latest items
|
||
- User confirms and adjusts
|
||
- Outputs: `outline.yaml` (items + config) + `fields.yaml` (field definitions)
|
||
|
||
#### Phase 2: Deep Research
|
||
```
|
||
/research/deep
|
||
```
|
||
- Parallel agents research each item (batch_size configurable)
|
||
- Each agent reads fields.yaml and outputs structured JSON
|
||
- Supports checkpoint resume
|
||
- Outputs: `results/*.json`
|
||
|
||
#### Optional: Expand Outline
|
||
```
|
||
/research/add-items # Add research targets via user input or web search
|
||
/research/add-fields # Add field definitions
|
||
```
|
||
|
||
#### Phase 3: Generate Report
|
||
```
|
||
/research/report
|
||
```
|
||
- Generates Python script to convert JSON to markdown
|
||
- User selects summary fields for TOC
|
||
- Skips uncertain values automatically
|
||
- Outputs: `report.md`
|
||
|
||
---
|
||
|
||
## 中文
|
||
|
||
> 灵感来源：[RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context](https://arxiv.org/abs/2511.18743)
|
||
|
||
Claude Code 的结构化调研工作流技能，支持两阶段调研：outline生成（可扩展）和深度调查。人在回路设计确保每个阶段的精确控制。
|
||
|
||
### 使用场景
|
||
|
||
- **学术研究**：论文综述、benchmark评测、文献分析
|
||
- **技术研究**：技术对比、框架评估、工具选型
|
||
- **市场研究**：竞品分析、行业趋势、产品比较
|
||
- **尽职调查**：公司研究、投资分析、风险评估
|
||
|
||
### 命令
|
||
|
||
| 命令 | 描述 |
|
||
|------|------|
|
||
| `/research` | 生成包含items和fields的调研outline |
|
||
| `/research/add-items` | 向现有outline添加更多items |
|
||
| `/research/add-fields` | 向现有outline添加更多fields |
|
||
| `/research/deep` | 使用并行agents对每个item进行深度调研 |
|
||
| `/research/report` | 从JSON结果生成markdown报告 |
|
||
|
||
### 安装
|
||
|
||
选择语言版本：
|
||
|
||
```bash
|
||
# 英文版
|
||
cp -r skills/research-en ~/.claude/skills/research
|
||
|
||
# 中文版
|
||
cp -r skills/research-zh ~/.claude/skills/research
|
||
|
||
# 必需：安装agent
|
||
cp agents/web-search-agent.md ~/.claude/agents/
|
||
```
|
||
|
||
### 工作流
|
||
|
||
#### 阶段1：生成Outline
|
||
```
|
||
/research <topic>
|
||
```
|
||
- 模型知识生成初始items和字段框架
|
||
- 网络搜索补充最新items
|
||
- 用户确认并调整
|
||
- 输出：`outline.yaml`（items + 配置）+ `fields.yaml`（字段定义）
|
||
|
||
#### 阶段2：深度调研
|
||
```
|
||
/research/deep
|
||
```
|
||
- 并行agents调研每个item（batch_size可配置）
|
||
- 每个agent读取fields.yaml并输出结构化JSON
|
||
- 支持断点续传
|
||
- 输出：`results/*.json`
|
||
|
||
#### 可选：扩展Outline
|
||
```
|
||
/research/add-items # 通过用户输入或网络搜索添加调研对象
|
||
/research/add-fields # 添加字段定义
|
||
```
|
||
|
||
#### 阶段3：生成报告
|
||
```
|
||
/research/report
|
||
```
|
||
- 生成Python脚本将JSON转换为markdown
|
||
- 用户选择目录中显示的摘要字段
|
||
- 自动跳过不确定值
|
||
- 输出：`report.md`
|
||
|
||
---
|
||
|
||
## References / 参考文献
|
||
|
||
- RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
|
||
|
||
## License / 许可证
|
||
|
||
MIT
|