deep-research

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

Try it — you'd type

“Help me with deep-research.”

And you'd get back

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

Formatted for Claude, no fluff, no preamble.

Works the same way every time you ask.

Adding it takes about 30 seconds

Click Get this skill. Grab the .md file, one click, no account needed.

Add it to Claude. Drop it into ~/.claude/skills/. Claude picks it up the next time you open a session.

Ask normally. Type your question. The skill triggers on the right keywords — you don't have to remember anything.

Unlock all skills — $25

You might also like

Migration Generator

Generate database migration files

Query Optimizer

Analyze and optimize slow database queries

Schema Designer

Design database schema from requirements

Seed Data Generator

Generate database seed/sample data

Index Advisor

Suggest database indexes based on query patterns

ORM Model Generator

Generate ORM models from database schema

SKILL FILEWhat Claude actually reads

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

## When to Use This Skill

Use this skill when:
- Performing market analysis
- Conducting competitive landscaping
- Creating literature reviews
- Doing technical research
- Performing due diligence
- Need detailed, cited research reports

## Requirements

- Python 3.8+
- httpx: `pip install -r requirements.txt`
- GEMINI_API_KEY environment variable

## Setup

1. Get a Gemini API key from [Google AI Studio](https://aistudio.google.com/)
2. Set the environment variable:
   ```bash
   export GEMINI_API_KEY=your-api-key-here
   ```
   Or create a `.env` file in the skill directory.

## Usage

### Start a research task
```bash
python3 scripts/research.py --query "Research the history of Kubernetes"
```

### With structured output format
```bash
python3 scripts/research.py --query "Compare Python web frameworks" \
  --format "1. Executive Summary\n2. Comparison Table\n3. Recommendations"
```

### Stream progress in real-time
```bash
python3 scripts/research.py --query "Analyze EV battery market" --stream
```

### Start without waiting
```bash
python3 scripts/research.py --query "Research topic" --no-wait
```

### Check status of running research
```bash
python3 scripts/research.py --status <interaction_id>
```

### Wait for completion
```bash
python3 scripts/research.py --wait <interaction_id>
```

### Continue from previous research
```bash
python3 scripts/research.py --query "Elaborate on point 2" --continue <interaction_id>
```

### List recent research
```bash
python3 scripts/research.py --list
```

## Output Formats

- **Default**: Human-readable markdown report
- **JSON** (`--json`): Structured data for programmatic use
- **Raw** (`--raw`): Unprocessed API response

## Cost & Time

| Metric | Value |
|--------|-------|
| Time | 2-10 minutes per task |
| Cost | $2-5 per task (varies by complexity) |
| Token usage | ~250k-900k input, ~60k-80k output |

## Best Use Cases

- Market analysis and competitive landscaping
- Technical literature reviews
- Due diligence research
- Historical research and timelines
- Comparative analysis (frameworks, products, technologies)

## Workflow

1. User requests research → Run `--query "..."`
2. Inform user of estimated time (2-10 minutes)
3. Monitor with `--stream` or poll with `--status`
4. Return formatted results
5. Use `--continue` for follow-up questions

## Exit Codes

- **0**: Success
- **1**: Error (API error, config issue, timeout)
- **130**: Cancelled by user (Ctrl+C)