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Learn-skills.dev 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 ...

install
source · Clone the upstream repo
git clone https://github.com/NeverSight/learn-skills.dev
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/NeverSight/learn-skills.dev "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/skills-md/aaaaqwq/agi-super-skills/deep-research" ~/.claude/skills/neversight-learn-skills-dev-deep-research-f30f8b && rm -rf "$T"
manifest: data/skills-md/aaaaqwq/agi-super-skills/deep-research/SKILL.md
source content

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 <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)