Gemini deep research

Skill ranbot-ai/awesome-skills/skills/gemini-deep-research

Awesome Claude Skills, Tools for Customizing Claude AI workflows

Install

npx -y skills add ranbot-ai/awesome-skills --skill gemini-deep-research

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Run autonomous multi-step research with Google's Gemini Deep Research Agent: kick off a query, poll progress, and collect a cited report for market analysis or literature reviews.

SKILL.md

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Gemini Deep Research Skill

When to Use

Use when a question needs autonomous multi-step research with cited sources (market analysis, literature reviews, competitive scans)
Use when you want to start a Gemini Deep Research run, poll its progress, and collect the final report
Use when a quick web search is not enough and a structured, source-grounded report is required

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

Get a Gemini API key from Google AI Studio
Set the environment variable:
```
export GEMINI_API_KEY=your-api-key-here
```
Or create a .env file in the skill directory.

Safety Gate

Before starting a research job, show the user the exact query, the fact that it will be sent to Google's Gemini service, the expected cost range, and the output destination. Start a job only after explicit approval. Do not include private workspace material, credentials, personal data, or confidential customer information in a query.

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

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

User requests research → Run --query "..."
Inform user of estimated time (2-10 minutes)
Monitor with --stream or poll with --status
Return formatted results
Use --continue for follow-up questions

Exit Codes

0: Success
1: Error (API error, config issue, timeout)
130: Cancelled by user (Ctrl+C)

Limitations

Each research job is a paid, third-party API request; costs and availability can change, and the listed estimate is not a spending authorization.
Reports may contain incomplete, stale, or incorrect citations. Verify consequential claims against primary sources.
This skill cannot guarantee that a prompt is safe to disclose; redact proprietary or personal material before requesting user approval.
An API key must remain local and must never be committed, printed, or sent in a query.