deep-research▌
sanjay3290/ai-skills · updated Apr 8, 2026
Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.
Gemini Deep Research Skill
Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.
Requirements
- Python 3.8+
- httpx:
pip install -r requirements.txt - GEMINI_API_KEY environment variable
Setup
- Get a Gemini API key from Google AI Studio
- Set the environment variable:
Or create aexport GEMINI_API_KEY=your-api-key-here.envfile 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
- User requests research → Run
--query "..." - Inform user of estimated time (2-10 minutes)
- Monitor with
--streamor poll with--status - Return formatted results
- Use
--continuefor follow-up questions
Exit Codes
- 0: Success
- 1: Error (API error, config issue, timeout)
- 130: Cancelled by user (Ctrl+C)
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★55 reviews- ★★★★★Henry Yang· Dec 28, 2024
I recommend deep-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Mateo Garcia· Dec 24, 2024
Keeps context tight: deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Carlos Johnson· Dec 24, 2024
deep-research reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Carlos Taylor· Nov 19, 2024
Keeps context tight: deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Emma Sanchez· Nov 15, 2024
I recommend deep-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Emma Menon· Nov 15, 2024
Registry listing for deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Jin Sethi· Oct 10, 2024
Registry listing for deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kaira Verma· Oct 6, 2024
deep-research reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Soo Liu· Oct 6, 2024
Keeps context tight: deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Alexander Anderson· Sep 25, 2024
I recommend deep-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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