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Get Started Free →This skill provides tooling and documentation to run, inspect, and extend the multi-agent LangGraph trading workflow in OpenClaw environments.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 52% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 32% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -8% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 2% | 0% |
This skill provides tooling and documentation to run, inspect, and extend the multi-agent LangGraph trading workflow in OpenClaw environments.
It includes a hard Risk Guard veto before any execution, structured tracing for transparency, and dedicated OpenClaw integration tools.
bash# From OpenClaw claw install https://github.com/olaxbt/ai-market-maker # Or locally git clone https://github.com/olaxbt/ai-market-maker.git cd ai-market-maker claw skill install ./openclaw
bash# Check dependencies ./openclaw/scripts/verify_installation.sh # Or python3 openclaw/scripts/claw_runner.py --verify
bash# Run backtest with default settings python3 openclaw/scripts/claw_runner.py --backtest # Paper trading python3 openclaw/scripts/claw_runner.py --paper --ticker BTC/USDT # Custom backtest python3 openclaw/scripts/claw_runner.py --backtest --symbols "BTC/USDT,ETH/USDT" --steps 150
The default settings use multiple symbols and conservative risk parameters:
Trade count: 17
Total return: 14.95%
Excess return vs BTC buy & hold: +30.25%
Sharpe ratio: 1.79
Maximum drawdown: 11.84%
Win rate: 62.5%These results are based on 100 days of historical data across BTC, ETH, and SOL, with full benchmark comparison and risk event logging.
bash# Paper trading with custom ticker claw run ai-market-maker --paper --ticker ETH/USDT # Backtesting with multiple symbols claw run ai-market-maker --backtest --symbols "BTC/USDT,ETH/USDT" --steps 150 # Installation verification claw run ai-market-maker --verify
Problem: ModuleNotFoundError: No module named 'talib' Solution:
bash# Recommended for environments without sudo conda install -y ta-lib -c conda-forge # Alternative: source compilation wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz tar -xzf ta-lib-0.4.0-src.tar.gz cd ta-lib/ ./configure --prefix=$HOME/.local make make install export LD_LIBRARY_PATH=$HOME/.local/lib:$LD_LIBRARY_PATH pip install ta-lib
Problem: ModuleNotFoundError: No module named 'agents.market_scanner' Solution:
bash# Install in development mode pip install -e . # Or set Python path export PYTHONPATH=/path/to/ai-market-maker/src:$PYTHONPATH
Problem: 429 Too Many Requests Solution:
.env for production useProblem: Environment variables not set Solution:
bash# Automatic configuration via claw_runner.py # Manual override: export NEXUS_API_KEY=your_key export AIMM_DESK_STRATEGY_PRESET=default
The repo exposes a lightweight, mostly read-only HTTP API:
GET /runs/latest → Latest run dataGET /runs/{run_id}/payload → Full payload of a runGET /runs/{run_id}/events → Events and tracesGET /pm/portfolio-health → Portfolio summaryGET /backtests → List backtest runsAIMM_API_KEY is not set → API is open (intended for local development only).AIMM_API_KEY is set → All non-local requests require x-api-key header.AIMM_CORS_ORIGINS appropriately.| Area | Location | Purpose | |------|----------|---------| | OpenClaw Runner | openclaw/scripts/claw_runner.py | Main entry point | | Installation Verifier | openclaw/scripts/verify_installation.sh | Dependency checker | | Skill Manifest | openclaw/manifest.json | OpenClaw skill definition | | Usage Examples | openclaw/examples/claw_usage.md | Usage guides | | Main Workflow | src/main.py | Core trading logic | | Agent System | src/agents/ | 7 trading desks | | Web Dashboard | web/ | Next.js monitoring UI |
STRATEGY_INTERVAL_SEC for lower resource usageWe welcome contributions! Please read the main CONTRIBUTING.md first.
bash# 1. Fork the repository # 2. Create a feature branch git checkout -b feature/improvement # 3. Make your changes # 4. Test with verification script ./openclaw/scripts/verify_installation.sh # 5. Submit Pull Request
README.mdopenclaw/examples/claw_usage.mdopenclaw/examples/korean_guide.mddocs/ directorydocs/ directory and openclaw/examples/Version: 1.0.0 Last Updated: 2026-04-17
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