gabrielmoreira/agent-skills-mirror/deep-research

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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.

Install

npx vskill@latest install gabrielmoreira/agent-skills-mirror/deep-research

SKILL.md

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:

``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

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)

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
19
Repository forks
2
7-day trend score
15

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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