Crypto Self-Learning

Crypto Self-Learning 🧠

AI-powered self-improvement 系统 for crypto trading. Learn from every trade to increase accuracy over time.

🎯 Core Concept

Every trade is a lesson. This 技能:

记录s every trade with full 上下文 Analyzes patterns in wins vs losses 生成s rules from real data 更新s memory automatically 📝 记录 a Trade

After EVERY trade (win or loss), 记录 it:

python3 {baseDir}/scripts/记录_trade.py \ --symbol BTCUSDT \ --direction LONG \ --entry 78000 \ --exit 79500 \ --pnl_percent 1.92 \ --leverage 5 \ --reason "RSI oversold + support bounce" \ --indicators '{"rsi": 28, "macd": "bullish_cross", "ma_position": "above_50"}' \ --market_上下文 '{"btc_trend": "up", "dxy": 104.5, "russell": "up", "day": "tuesday", "hour": 14}' \ --结果 WIN \ --notes "清理 设置up, followed the plan"

Required Fields: Field Description Example --symbol Trading pAIr BTCUSDT --direction LONG or SHORT LONG --entry Entry price 78000 --exit Exit price 79500 --pnl_percent Profit/Loss % 1.92 or -2.5 --结果 WIN or LOSS WIN Optional but Recommended: Field Description --leverage Leverage used --reason Why you entered --indicators JSON with indicators at entry --market_上下文 JSON with macro conditions --notes Post-trade observations 📊 Analyze Performance

运行 analysis to discover patterns:

python3 {baseDir}/scripts/analyze.py

输出s:

Win rate by direction (LONG vs SHORT) Win rate by day of week Win rate by RSI ranges Win rate by leverage Best/worst 设置ups identified Suggested rules Analyze Specific 过滤器s: python3 {baseDir}/scripts/analyze.py --symbol BTCUSDT python3 {baseDir}/scripts/analyze.py --direction LONG python3 {baseDir}/scripts/analyze.py --min-trades 10

🧠 生成 Rules

提取 actionable rules from your trade 历史:

python3 {baseDir}/scripts/生成_rules.py

This analyzes patterns and 输出s rules like:

🚫 AVOID: LONG when RSI > 70 (win rate: 23%, n=13) ✅ PREFER: SHORT on Mondays (win rate: 78%, n=9) ⚠️ CAUTION: Trades with leverage > 10x (win rate: 35%, n=20)

📈 Auto-更新 Memory

应用ly learned rules to 代理 memory:

python3 {baseDir}/scripts/更新_memory.py --memory-path /path/to/MEMORY.md

This 应用ends a "## 🧠 Learned Rules" section with data-driven insights.

Dry 运行 (preview changes): python3 {baseDir}/scripts/更新_memory.py --memory-path /path/to/MEMORY.md --dry-运行

📋 View Trade 历史 python3 {baseDir}/scripts/记录_trade.py --列出 python3 {baseDir}/scripts/记录_trade.py --列出 --last 10 python3 {baseDir}/scripts/记录_trade.py --stats

🔄 Weekly Review

运行 weekly to see 进度:

python3 {baseDir}/scripts/weekly_review.py

生成s:

This week's performance vs last week New patterns discovered Rules that worked/fAIled Recommendations for next week 📁 Data Storage

Trades are stored in {baseDir}/data/trades.json:

{ "trades": [ { "id": "uuid", "timestamp": "2026-02-02T13:00:00Z", "symbol": "BTCUSDT", "direction": "LONG", "entry": 78000, "exit": 79500, "pnl_percent": 1.92, "结果": "WIN", "indicators": {...}, "market_上下文": {...} } ] }

🎯 Best Practices 记录 EVERY trade - Wins AND losses Be honest - Don't skip bad trades 添加 上下文 - More data = better patterns Review weekly - Patterns emerge over time Trust the data - If data says avoid something, AVOID IT 🔗 Integration with tess-cripto

添加 to tess-cripto's 工作流:

Before trade: 检查 rules in MEMORY.md After trade: 记录 with full 上下文 Weekly: 运行 analysis and 更新 memory

技能 by Total Easy Software - Learn from every trade 🧠📈