openclaw-workspace

Summary

An advanced OpenClaw workspace focused on automating trading across multiple markets, managing digital products, and integrating with a Telegram bot. This workspace provides a suite of quant trading systems, strategy modules, project templates, memory and agent management, and local customization tools, all written in Python.

Included Assets

• Workspace Core

  • AGENTS.md: Guidelines for agent operation and memory usage.
  • MEMORY.md: Long-term memory, workflow, and important settings.
  • SOUL.md: Core philosophy, principles, assistant persona.
  • TOOLS.md: Local environment notes (API keys, SSH, TTS, device config).

• Trading Systems

  • a-share-trading-system/: Unified A-share trading system (multi-strategy, reporting, risk controls).
  • okx-trading-system/: Automated OKX crypto quant system (multi-strategy voting, cron tasks, dashboard).
  • quant-trading-system/: Multi-market quant system (A-shares, HK, Crypto, daily rebalancing).
  • quant-trading/: Short-term stock selection strategies (network/data issues & solutions).
  • polymarket-fast-loop/: Automated fast-loop trading system for Polymarket prediction markets.
  • polymarket-quant-bot/: Quant bot for Polymarket, using five mathematical models.
  • polymarket-trading-system/: Unified trading system for Polymarket with three distinct strategies.
  • agents/timezone-arbitrage/: Timezone arbitrage agent for exploiting event timing edge in prediction markets.

• Opportunities & Projects

  • opportunities/: Opportunity discovery and execution engine, with reports, plans, and action logs.
  • projects/shopify-dropshipping/: Shopify dropshipping project plan and automation playbook.

• Skills & Extensions

  • skills/day-trading-pro/: Day trading assistant (technical analysis, risk, psychology).
  • skills/stock-market-pro/quant-trading-backtrader/: Backtrader-based strategy research and backtesting.
  • skills/stock-market-pro/quant-trading-system/: Automated quant trading with four-strategy voting.
  • skills/stock-market-pro/tradingview-quant/: Quant analysis skillset based on TradingView data.

How to Use

1. Read Workspace Guidelines

   • Start with AGENTS.md, then SOUL.md to understand your operation rules and persona.
   • Use MEMORY.md for key workflow decisions and settings.

2. Configure Trading Systems

   • Each trading or agent module has its own README.md for specific setup, dependencies, and quickstart instructions.
   • Edit relevant config files (e.g. config.json, .yaml) before launching systems.
   • Many systems support simulation mode. Start here before live trading.

3. Run Automated Bots

   • Most trading bots are run via Python scripts: launch from their folder per instructions.
   • For Telegram integration and notifications, configure bot tokens and chat IDs as shown in respective config examples.

4. Leverage Project Templates

   • Shopify project framework provides step-by-step automation for launching digital product stores.

5. Use Extension Skills

   • Skills in the skills/ directory extend analysis, backtesting, or trading automation capabilities. Import and use as Python modules or as plug-ins where required.

6. Customize with TOOLS.md

   • Record and update your local device and credential info here to keep the workspace portable and secure.

Notes

• Security & Privacy: Personal and sensitive info should be managed with care (see MEMORY.md and TOOLS.md for handling secrets and configurations).
• Language: Many system and doc files include Chinese, especially for strategy breakdowns, workflows, and diagnostics.
• Modular Architecture: Each system (trading, project, agent) can be used independently. Review their individual documentation for details.
• Automation: Cron jobs and automation are pre-configured for several systems—verify schedules and paths according to your OS/environment.
• Telegram Bot: Set your own bot tokens and chat ID before launch—these are not provided.
• Simulation Mode: Strongly recommended to test all trading bots in simulation mode before using real capital.
• Python Version: Most systems require Python 3.10+, check each module for further dependencies.
• Local Customization: Use TOOLS.md for local paths, device aliases, and private API key management.
• No Unsupported Features: Only documented capabilities are included; external integrations and features depend on your configuration.

For detailed, module-specific instructions, consult each included subfolder's README.md.