trading-coach

What This Skill Does

Trading Coach is an advanced AI-powered analytical tool designed to transform raw brokerage transaction data into actionable financial intelligence. Instead of manually tracking P&L, this skill ingests exported CSVs from major brokerages like Futu, Tiger, CITIC, and Huatai to perform sophisticated FIFO (First-In-First-Out) position matching. It evaluates your performance across 8 critical dimensions—including entry quality, risk management, and trend alignment—to calculate a precise trading score. Beyond simple arithmetic, it leverages AI to provide deep-dive insights into your behavioral patterns, identifying common mistakes like trend-chasing or impulsive exits. The objective is to replace speculative "gut-feeling" trading with data-driven refinement, helping you visualize your trading strengths and weaknesses.

Installation

To integrate Trading Coach into your OpenClaw environment, use the following terminal command: clawhub install openclaw/skills/skills/benzema216/trading-coach Once installed, ensure your local directory is configured by following the instructions in the config_template.py file to handle your specific data formatting requirements.

Use Cases

• Professional Performance Audit: Monthly or quarterly reviews of trading logs to identify profit leakage.
• Behavioral Correction: Identifying psychological biases, such as overtrading during market volatility or premature profit-taking.
• Risk Management Review: Analyzing whether your stop-loss and take-profit ratios align with your stated risk tolerance.
• Strategy Validation: Checking if specific technical indicators (like RSI or MACD) actually correlate with profitable exits in your historical data.

Example Prompts

1. "帮我复盘一下我上个月的交易，重点分析我的入场逻辑和亏损的主要原因。"
2. "这是我的导出交易记录CSV，请帮我分析盈亏统计，并指出我有哪些明显的交易模式问题。"
3. "我想提升交易质量，请评估我最近的持仓表现并提供具体的改进建议。"

Tips & Limitations

• Data Integrity: Ensure the CSV exported from your brokerage is in its original, raw format for accurate FIFO matching. Modified files may cause parsing errors.
• Timeframes: The accuracy of the 8-dimension score depends on the sample size; a minimum of 20-30 trades is recommended for a statistically significant analysis.
• Contextual Awareness: While the AI provides excellent behavioral insights, it cannot account for external life stressors; always combine these technical reports with your personal market diary for the best results.
• Security: Since this tool processes sensitive financial data, always review the generated insights locally before sharing them with third-party platforms.