Crypto Self-Learning

# Crypto Self-Learning 🧠

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

## 🎯 Core Concept

Every trade is a lesson. This skill: 1. **Logs** every trade with full context 2. **Analyzes** patterns in wins vs losses 3. **Generates** rules from real data 4. **Updates** memory automatically

## 📝 Log a Trade

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

```bash python3 {baseDir}/scripts/log_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_context '{"btc_trend": "up", "dxy": 104.5, "russell": "up", "day": "tuesday", "hour": 14}' \ --result WIN \ --notes "Clean setup, 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 | | `--result` | WIN or LOSS | WIN |

### Optional but Recommended: | Field | Description | |-------|-------------| | `--leverage` | Leverage used | | `--reason` | Why you entered | | `--indicators` | JSON with indicators at entry | | `--market_context` | JSON with macro conditions | | `--notes` | Post-trade observations |

## 📊 Analyze Performance

Run analysis to discover patterns:

```bash python3 {baseDir}/scripts/analyze.py ```

Outputs: - Win rate by direction (LONG vs SHORT) - Win rate by day of week - Win rate by RSI ranges - Win rate by leverage - Best/worst setups identified - Suggested rules

### Analyze Specific Filters: ```bash python3 {baseDir}/scripts/analyze.py --symbol BTCUSDT python3 {baseDir}/scripts/analyze.py --direction LONG python3 {baseDir}/scripts/analyze.py --min-trades 10 ```

## 🧠 Generate Rules

Extract actionable rules from your trade history:

```bash python3 {baseDir}/scripts/generate_rules.py ```

This analyzes patterns and outputs 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-Update Memory

Apply learned rules to agent memory:

```bash python3 {baseDir}/scripts/update_memory.py --memory-path /path/to/MEMORY.md ```

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

### Dry Run (preview changes): ```bash python3 {baseDir}/scripts/update_memory.py --memory-path /path/to/MEMORY.md --dry-run ```

## 📋 View Trade History

```bash python3 {baseDir}/scripts/log_trade.py --list python3 {baseDir}/scripts/log_trade.py --list --last 10 python3 {baseDir}/scripts/log_trade.py --stats ```

## 🔄 Weekly Review

Run weekly to see progress:

```bash python3 {baseDir}/scripts/weekly_review.py ```

Generates: - 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`: ```json { "trades": [ { "id": "uuid", "timestamp": "2026-02-02T13:00:00Z", "symbol": "BTCUSDT", "direction": "LONG", "entry": 78000, "exit": 79500, "pnl_percent": 1.92, "result": "WIN", "indicators": {...}, "market_context": {...} } ] } ```

## 🎯 Best Practices

1. **Log EVERY trade** - Wins AND losses 2. **Be honest** - Don't skip bad trades 3. **Add context** - More data = better patterns 4. **Review weekly** - Patterns emerge over time 5. **Trust the data** - If data says avoid something, AVOID IT

## 🔗 Integration with tess-cripto

Add to tess-cripto's workflow: 1. Before trade: Check rules in MEMORY.md 2. After trade: Log with full context 3. Weekly: Run analysis and update memory

--- *Skill by Total Easy Software - Learn from every trade* 🧠📈