/deep-research

name: deep-research
description: "Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports."
metadata:
  risk: safe
  source: "https://github.com/sanjay3290/ai-skills/tree/main/skills/deep-research"
  date_added: "2026-02-27"

Gemini Deep Research Skill

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:

   export GEMINI_API_KEY=your-api-key-here

Or create a `.env` file in the skill directory.

Usage

Start a research task

python3 scripts/research.py --query "Research the history of Kubernetes"

With structured output format

python3 scripts/research.py --query "Compare Python web frameworks" \
  --format "1. Executive Summary\n2. Comparison Table\n3. Recommendations"

Stream progress in real-time

python3 scripts/research.py --query "Analyze EV battery market" --stream

Start without waiting

python3 scripts/research.py --query "Research topic" --no-wait

Check status of running research

python3 scripts/research.py --status <interaction_id>

Wait for completion

python3 scripts/research.py --wait <interaction_id>

Continue from previous research

python3 scripts/research.py --query "Elaborate on point 2" --continue <interaction_id>

List recent research

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)