sanjay3290/ai-skillsApache-2.06 files

Deep Research

Name: Deep Research
Availability: InStock
Author: sanjay3290

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.

Use this skill View repository View on skills.sh

Specification

Skill ID: sanjay3290/ai-skills/deep-research
Publisher: sanjay3290
Repository: ai-skills
Installs: 0
Files: 6
License: Apache-2.0
Synced: Sep 23, 2026

How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

sanjay3290/ai-skills/deep-researchInstalls these files

.env.example
.gitignore
README.md
SKILL.md
requirements.txt
scripts/research.py

What this skill tells the agent

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

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)

Use this skill in a project

Open any RiverX project, search the Skills panel for sanjay3290/ai-skills/deep-research, and install it in one click.

Use this skill