Skill v1.0.0

Automated scan

sanjay3290/ai-skills/deep-research

──Details

PublishedMarch 26, 2026 at 05:15 AM

Content Hashsha256:e3b0c44298fc1c14...

Git SHAdiscovery:16

──Files

Files (1 file, 2.7 KB)

SKILL.md2.7 KBactive

SKILL.md · 108 lines · 2.7 KB

version: "1.0.0" name: deep-research description: "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." license: Apache-2.0 metadata: author: sanjay3290 version: "1.0"

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

Get a Gemini API key from Google AI Studio
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

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)

All versions v1.0.1 →