Deep Research
- 11 installs
- 82 repo stars
- Updated August 2, 2026
- aaaaqwq/agi-super-skills
deep-research is a Claude Code skill that runs autonomous multi-step research tasks through Google Gemini's Deep Research API and returns cited markdown reports.
About
deep-research is a Claude Code skill that runs autonomous multi-step research using Google Gemini's Deep Research Agent. A developer uses it for market analysis, competitive landscaping, literature reviews, and due diligence that need cited reports. It plans, searches, reads, and synthesizes over 2-10 minutes per task via a bundled Python script.
- Autonomous multi-step research via the Gemini Deep Research Agent
- Produces cited market analysis, competitive landscaping, and due-diligence reports
- Streaming, status polling, and follow-up continuation via a Python CLI
Deep Research by the numbers
- 11 all-time installs (skills.sh)
- Ranked #11,696 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 3, 2026 (Skillselion catalog sync)
deep-research capabilities & compatibility
Requires a Gemini API key; docs state $2-5 per research task.
- Capabilities
- research · web search · orchestration
- Works with
- gcp
- Use cases
- research · web search
- Runs
- Runs locally
- Pricing
- Bring your own API key
What deep-research says it does
Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.
GEMINI_API_KEY environment variable
npx skills add https://github.com/aaaaqwq/agi-super-skills --skill deep-researchAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 11 |
|---|---|
| repo stars | ★ 82 |
| Last updated | August 2, 2026 |
| Repository | aaaaqwq/agi-super-skills ↗ |
What it does
Run autonomous multi-step research reports (market analysis, competitive landscaping, due diligence) via the Gemini Deep Research API.
Who is it for?
Market analysis, competitive landscaping, literature reviews, and due diligence needing cited reports.
Skip if: Quick single-shot lookups where a 2-10 minute research run is overkill.
When should I use this skill?
You need a deep, cited research report and can wait 2-10 minutes for the Gemini agent to finish.
What you get
A cited, synthesized research report generated autonomously by the Gemini Deep Research Agent.
- Cited markdown research report
- JSON or raw API output
By the numbers
- 2-10 minutes per task
- $2-5 cost per task
- ~250k-900k input tokens per task
Files
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 2. Set the environment variable:
export GEMINI_API_KEY=your-api-key-hereOr 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" --streamStart without waiting
python3 scripts/research.py --query "Research topic" --no-waitCheck 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 --listOutput 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)
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How long does a research task take?
The docs state 2-10 minutes per task, with cost of $2-5 per task varying by complexity.
What API key does it need?
It requires a GEMINI_API_KEY environment variable from Google AI Studio.