Skill: zero2ai-hub/skill-trading-journal (version 1.0.0)

--- 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)