Trading Journal Ai

---
name: skill-trading-journal
description: Log every trade with full context (thesis, entry, exit, PnL, emotion, lesson). Generate weekly and monthly performance reports. Identify patterns in wins/losses. Use when recording a new trade, reviewing performance, running a weekly debrief, or updating the trading strategy based on results.
---

# Trading Journal

Systematic trade logging and performance review. Every trade logged = strategy gets smarter over time.

## Trade Log Storage

Stored at: `~/.openclaw/workspace/trading/journal.json`

## Log a New Trade

```
Log trade to trading/journal.json:
- Symbol: GRASSUSDT
- Direction: LONG
- Entry: $0.36
- Entry date: 2026-03-13
- Size: $50 USDC
- Thesis: Price broke above $0.30 threshold + GTC keynote catalyst in 3 days + volume rising
- Catalyst: NVIDIA GTC 2026
- Signal source: skill-crypto-threshold-watcher
- Stop loss: $0.28 (22% below entry)
- Take profit: $0.50 (39% above entry)
```

## Log Trade Exit

```
Update journal entry [trade-id] with exit:
- Exit price: $0.46
- Exit date: 2026-03-17
- Exit reason: Take profit not hit, manual exit (Aladdin decision)
- PnL: +$12.78 (+27.7%)
- Lesson: Entry thesis was correct. Exit was early — could have held to $0.50 TP.
```

## Trade Record Schema

```json
{
  "id": "trade-001",
  "symbol": "GRASSUSDT",
  "direction": "LONG",
  "status": "CLOSED",
  "entry_price": 0.36,
  "entry_date": "2026-03-13",
  "entry_size_usdc": 50,
  "thesis": "Price broke above $0.30 threshold + GTC keynote catalyst",
  "catalyst": "NVIDIA GTC 2026",
  "signal_source": "skill-crypto-threshold-watcher",
  "stop_loss": 0.28,
  "take_profit": 0.50,
  "exit_price": 0.46,
  "exit_date": "2026-03-17",
  "exit_reason": "Manual exit — pre-TP",
  "pnl_usdc": 12.78,
  "pnl_pct": 27.7,
  "lesson": "Exit was early. Hold to TP next time unless thesis breaks.",
  "emotion": "neutral",
  "thesis_correct": true,
  "execution_correct": false
}
```

## Weekly Performance Report

```
Generate weekly trading report from trading/journal.json for the past 7 days.
Include: total PnL, win rate, avg win vs avg loss, best/worst trade, lessons summary, strategy adjustments.
```

**Sample output:**
```
📊 WEEKLY TRADING REPORT — Mar 10–17, 2026

Trades: 2 | Wins: 2 | Losses: 0 | Win Rate: 100%
Total PnL: +$18.43 (+23.4% on deployed capital)
Avg Win: +$9.21 | Avg Loss: N/A
Best Trade: GRASSUSDT +$12.78 (+27.7%)

LESSONS THIS WEEK:
- Thesis-correct but execution left early on GRASS — hold to TP when thesis intact
- Volume spike threshold ($100M) on FET called the move correctly

STRATEGY ADJUSTMENTS:
- Raise FET volume threshold to $120M (reduce false positives)
- Add trailing stop at +20% to avoid leaving gains on table

NEXT WEEK CATALYSTS:
- [from catalyst-calendar]
```

## Monthly Strategy Review

```
Generate monthly strategy review from trading/journal.json.
Identify: which signal types worked, which failed, regime conditions, recommended rule updates.
```

## Integration with Trading Pipeline

- **Inputs from:** `skill-crypto-threshold-watcher` (signal), `skill-catalyst-calendar` (context), `binance-pro` (execution confirmation)
- **Outputs to:** `backtest-expert` (validated signals for re-testing), `quant-trading-system` (parameter updates)
- **Review cadence:** Weekly debrief every Sunday 20:00 UTC

## Emotion Tracking

Log emotion at trade entry: `calm | excited | fearful | greedy | neutral`

Over time, identify if emotional state correlates with win/loss rate. This is where most traders lose edge.

## Rules Enforcement

Before logging a new trade, verify:
- [ ] Thesis stated in one sentence
- [ ] Stop-loss defined
- [ ] Take-profit defined
- [ ] Position size within rulebook limits
- [ ] Catalyst identified (or "none — pure technical")

If any field missing → trade is NOT valid per rulebook.