OpenSkillIndex← back to search
claude-coderesearch

Antigravity-awesome-skills deep-research

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

install
source · Clone the upstream repo
git clone https://github.com/sickn33/antigravity-awesome-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sickn33/antigravity-awesome-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/antigravity-awesome-skills/skills/deep-research" ~/.claude/skills/sickn33-antigravity-awesome-skills-deep-research-7ca511 && rm -rf "$T"
manifest: plugins/antigravity-awesome-skills/skills/deep-research/SKILL.md
tags
#research#data-analysis#report-generation#information-synthesis
safety · automated scan (medium risk)
This is a pattern-based risk scan, not a security review. Our crawler flagged:
  • pip install
  • references .env files
  • references API keys
Always read a skill's source content before installing. Patterns alone don't mean the skill is malicious — but they warrant attention.
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)

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.