據 AlphaMoat 統計,截至 2026-09,Trading Journal 累計下載 3,969 次、獲 2 個星標,在全部 5,078 個 AI 技能中排名第 2,592 位,在「資料分析」分類(399 個)中排名第 199 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 123 | 3969 | 2 | - |
| SkillHub ↗ | 119 | 3750 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
主文給出本地 JSON 日誌路徑與記錄結構,要求新交易包含論點、止損、止盈、倉位規則和催化因素;週報與月度覆盤用於識別模式並提出策略調整。交易記錄和建議可能影響決策,且日誌含敏感財務資訊,應保護本地檔案並在採取任何策略調整前自行稽核。
資料釋出於 2026-10-29
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3969 | — | 2 |
| 2026-08 | 3842 | +6.8% | 2 |
| 2026-07 | 3599 | +16.6% | 2 |
| 2026-06 | 3086 | +7.7% | 2 |
| 2026-05 | 2866 | — | 2 |
| 2026-03 | 1585 | — | 1 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- 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.
AdMapix 的取數層:把廣告與應用相關的查詢轉成介面呼叫,只回原始 JSON。
透過 Tavily 搜尋公開網頁,並回傳含連結與摘要的結構化結果。
把資料庫、表格與匯出的原始資料變成可決策結論的資料分析技能。
用 Yahoo Finance 資料做股票與加密貨幣分析、組合跟蹤的技能。
管理本地自選股清單,並按代碼彙總同花順行情與近期表現的技能。
知了標訊:查詢和分析招標、中標、供應商與採購市場資訊。
用命令列監控部落格與 RSS/Atom 源的更新。
彙總 Codex 或 Claude 按模型計費的使用成本。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。