Agent skill

deep-research

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 minutes but produces detailed, cited reports. Costs $2-5 per task.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/sanjay3290/ai-skills/tree/main/skills/deep-research

Metadata

Additional technical details for this skill

author
sanjay3290
version
1.0

SKILL.md

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

  1. Get a Gemini API key from Google AI Studio
  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)

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