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.
Add this skill
npx mdskills install sanjay3290/deep-researchWell-documented wrapper for Gemini API research with clear cost/time expectations and async workflows
Execute autonomous multi-step research tasks using Google's Gemini Deep Research Agent. Unlike standard LLM queries that respond in seconds, Deep Research is an "analyst-in-a-box" that plans, searches, reads, and synthesizes information into comprehensive, cited reports.
The Deep Research Agent (deep-research-pro-preview-12-2025) powered by Gemini 3 Pro:
This process takes 2-10 minutes but produces thorough analysis that would take a human researcher hours.
# Navigate to skill directory
cd skills/deep-research
# Install dependencies
pip install -r requirements.txt
# Set up API key
cp .env.example .env
# Edit .env and add your GEMINI_API_KEY
.env file# Basic research query
python3 scripts/research.py --query "Research the competitive landscape of cloud providers in 2024"
# Stream progress in real-time
python3 scripts/research.py --query "Compare React, Vue, and Angular frameworks" --stream
# Get structured JSON output
python3 scripts/research.py --query "Analyze the EV market" --json
--query / -qStart a new research task.
# Basic query
python3 scripts/research.py -q "Research the history of containerization"
# With output format specification
python3 scripts/research.py -q "Compare database solutions" \
--format "1. Executive Summary\n2. Comparison Table\n3. Pros/Cons\n4. Recommendations"
# Start without waiting for results
python3 scripts/research.py -q "Research topic" --no-wait
--streamStream research progress in real-time. Shows thinking steps and builds the report as it's generated.
python3 scripts/research.py -q "Analyze market trends" --stream
--status / -sCheck the status of a running research task.
python3 scripts/research.py --status abc123xyz
--wait / -wWait for a specific research task to complete.
python3 scripts/research.py --wait abc123xyz
--continueContinue a conversation from previous research. Useful for follow-up questions.
# First, run initial research
python3 scripts/research.py -q "Research Kubernetes architecture"
# Output: Interaction ID: abc123xyz
# Then ask follow-up
python3 scripts/research.py -q "Elaborate on the networking section" --continue abc123xyz
--list / -lList recent research tasks from local history.
python3 scripts/research.py --list
python3 scripts/research.py --list --limit 20
| Flag | Description |
|---|---|
| (default) | Human-readable markdown report |
--json / -j | Structured JSON output |
--raw / -r | Raw API response |
| Variable | Default | Description |
|---|---|---|
GEMINI_API_KEY | (required) | Your Google Gemini API key |
DEEP_RESEARCH_TIMEOUT | 600 | Max wait time in seconds |
DEEP_RESEARCH_POLL_INTERVAL | 10 | Seconds between status polls |
DEEP_RESEARCH_CACHE_DIR | ~/.cache/deep-research | Local history cache directory |
GEMINI_API_KEY=your-api-key-here
DEEP_RESEARCH_TIMEOUT=600
DEEP_RESEARCH_POLL_INTERVAL=10
Deep Research uses a pay-as-you-go model based on token usage:
| Task Type | Search Queries | Input Tokens | Output Tokens | Estimated Cost |
|---|---|---|---|---|
| Standard | ~80 | ~250k (50-70% cached) | ~60k | $2-3 |
| Complex | ~160 | ~900k (50-70% cached) | ~80k | $3-5 |
python3 scripts/research.py -q "Analyze the competitive landscape of \
EV battery manufacturers, including market share, technology, and supply chain"
python3 scripts/research.py -q "Compare Rust vs Go for building \
high-performance backend services" \
--format "1. Performance Benchmarks\n2. Memory Safety\n3. Ecosystem\n4. Learning Curve"
python3 scripts/research.py -q "Research Company XYZ: recent news, \
financial performance, leadership changes, and market position"
python3 scripts/research.py -q "Review recent developments in \
large language model efficiency and optimization techniques"
| Error | Cause | Solution |
|---|---|---|
GEMINI_API_KEY not set | Missing API key | Set in .env or environment |
API error 429 | Rate limited | Wait and retry |
Research timed out | Task took too long | Simplify query or increase timeout |
Failed to parse result | Unexpected response | Use --raw to see actual output |
| Code | Meaning |
|---|---|
| 0 | Success |
| 1 | Error (API, config, timeout) |
| 130 | Cancelled by user (Ctrl+C) |
┌─────────────────┐ ┌──────────────────────┐
│ CLI Script │──────│ DeepResearchClient │
│ (research.py) │ │ │
└─────────────────┘ └──────────┬───────────┘
│
▼
┌──────────────────────┐
│ Gemini Deep │
│ Research API │
│ │
│ POST /interactions │
│ GET /interactions │
└──────────────────────┘
│
▼
┌──────────────────────┐
│ HistoryManager │
│ (~/.cache/deep- │
│ research/) │
└──────────────────────┘
Install via CLI
npx mdskills install sanjay3290/deep-researchDeep Research is a free, open-source AI agent skill. 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 Deep Research with a single command:
npx mdskills install sanjay3290/deep-researchThis downloads the skill files into your project and your AI agent picks them up automatically.
Deep Research works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.