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.
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/) │
└──────────────────────┘
npx skills add sanjay3290/deep-research下载完整 Skill 目录，包含 SKILL.md 及所有相关文件
Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs.
Manage Apple Notes via the `memo` CLI on macOS (create, view, edit, delete, search, move, and export notes). Use when a user asks OpenClaw to add a note, list notes, search notes, or manage note folders.
Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.
Use when you need to control Slack from OpenClaw via the slack tool, including reacting to messages or pinning/unpinning items in Slack channels or DMs.
Manage Apple Reminders via remindctl CLI (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.
Manage Trello boards, lists, and cards via the Trello REST API.
Category:productivity