Deep Research Gemini

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name: deep-research description: "Execute autonomous multi-step research using Google Gemini Deep Research Agent. Use for: market analysis, competitive landscaping, literature reviews, technical research, due diligence. Takes 2-10 ..." risk: safe source: "https://github.com/sanjay3290/ai-skills/tree/main/skills/deep-research" date_added: "2026-02-27"

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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-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 

Wait for completion

python3 scripts/research.py --wait 

Continue from previous research

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

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)

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 

Wait for completion

python3 scripts/research.py --wait 

Continue from previous research

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

List recent research

python3 scripts/research.py --list

1. Get a Gemini API key from Google AI Studio 2. Set the environment variable:

   export GEMINI_API_KEY=your-api-key-here
   

Or create a .env file in the skill directory.