jilinchenandClaude Opus 4.5
f0348451af
- Add items_per_agent field to control items per agent - Confirm via AskUserQuestion in /research phase - Deep research reads from outline config directly 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
97 lines
2.6 KiB
Markdown
97 lines
2.6 KiB
Markdown
# Deep Research Skill for Claude Code
|
|
|
|
> 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 |
|
|
|
|
## Installation
|
|
|
|
Copy the `skills/` folder to your Claude Code directory:
|
|
|
|
```bash
|
|
cp -r skills/* ~/.claude/skills/
|
|
```
|
|
|
|
## Workflow
|
|
|
|
### Phase 1: Generate Outline
|
|
```
|
|
/research <topic>
|
|
```
|
|
- Uses model knowledge + web search
|
|
- Asks for existing field definitions
|
|
- Creates `{topic}/` directory with separated files
|
|
|
|
### Phase 2: Deep Research
|
|
```
|
|
/research/deep
|
|
```
|
|
- Reads outline and fields automatically from current directory
|
|
- Launches parallel agents (5 per batch)
|
|
- Agents read fields.yaml independently (not passed in prompt)
|
|
- Outputs structured JSON per item
|
|
- Supports resume from checkpoint
|
|
|
|
### Optional: Expand Outline
|
|
```
|
|
/research/add-items # Add more research targets
|
|
/research/add-fields # Add more field definitions
|
|
```
|
|
|
|
## Output Format
|
|
|
|
### Directory Structure
|
|
```
|
|
{topic}/
|
|
├── outline.yaml # items + execution config
|
|
├── fields.yaml # field definitions
|
|
└── results/ # deep research outputs
|
|
```
|
|
|
|
### outline.yaml
|
|
```yaml
|
|
topic: "your topic"
|
|
items:
|
|
- name: "Item1"
|
|
source: "source info"
|
|
execution:
|
|
batch_size: 5 # parallel agents (default: 5)
|
|
items_per_agent: 1 # items per agent (default: 1)
|
|
output_dir: "./results" # output directory (default: ./results)
|
|
```
|
|
|
|
### fields.yaml
|
|
```yaml
|
|
basic_info:
|
|
- name: "field_name"
|
|
description: "field description"
|
|
detail_level: "detailed|brief"
|
|
```
|
|
|
|
### Research Result (JSON)
|
|
Each item outputs a structured JSON file with all defined fields.
|
|
|
|
## References
|
|
|
|
- RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
|
|
|
|
## License
|
|
|
|
MIT
|