Index live · v1.3.0 · MAY 30 2026

Deep Research

B-rank
bysanjay3290

Deep Research by sanjay3290 runs autonomous, multi-step research via Google's Gemini Deep Research API and returns thorough, cited reports. The skill executes a local Python script that calls only Google's official generativelanguage API (no remote code fetch, no shell-out), reads its key from GEMINI_API_KEY, and is transparent about cost (~$2–5/task, 2–10 min). Requires a paid Gemini API key.

Claude CodeClaude Ai
297stars
Updated 3 months ago
1contributor

Install This Skill

npx skills add sanjay3290/deep-research

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: 
    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

MetricValue
Time2-10 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)
Synced from sanjay3290/ai-skills@1fce823fetched May 30, 2026

When to use this skill

  • →Autonomous, multi-step research that returns a thorough, cited report
  • →Topics deep enough to justify a 2–10 minute agentic run
  • →Producing a sourced briefing you'll hand to a writer or strategist

When not to use

  • ✕Quick factual lookups — the agentic run is overkill (and metered)
  • ✕Workflows where you can't provision a paid Gemini API key
  • ✕Tasks needing live site scraping — pair with `firecrawl-cli` for that

Frequently asked questions

Quick Stats

Source repo · this path
Stars297
Forks26
Last commit2026-02-19
Contributors1
LicenseApache-2.0
CategoryAI/ML Development
View on GitHub

Author

s

sanjay3290

@sanjay3290

Tags

researchgeminiagentcitationsreports