据 AlphaMoat 统计,截至 2026-09,Trading Journal 累计下载 3,969 次、获 2 个星标,在全部 5,078 个 AI 技能中排名第 2,592 位,在「数据分析」分类(399 个)中排名第 199 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 123 | 3,969 | 2 | - |
| SkillHub ↗ | 119 | 3,750 | 2 | — |
各平台的计数口径不同,统计时间不一致。
主文给出本地 JSON 日志路径与记录结构,要求新交易包含论点、止损、止盈、仓位规则和催化因素;周报与月度复盘用于识别模式并提出策略调整。交易记录和建议可能影响决策,且日志含敏感财务信息,应保护本地文件并在采取任何策略调整前自行审核。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,969 | — | 2 |
| 2026-08 | 3,842 | +6.8% | 2 |
| 2026-07 | 3,599 | +16.6% | 2 |
| 2026-06 | 3,086 | +7.7% | 2 |
| 2026-05 | 2,866 | — | 2 |
| 2026-03 | 1,585 | — | 1 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 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 的取数层:把广告与应用相关的查询转成接口调用,只回原始 JSON。
走 Tavily 检索公开网页,返回带链接与摘要的结构化结果。
把数据库、表格与导出的原始数据变成可决策结论的数据分析技能。
用 Yahoo Finance 数据做股票与加密货币分析、组合跟踪的技能。
管理本地自选股清单,并按代码汇总同花顺行情与近期表现的技能。
知了标讯:查询和分析招标、中标、供应商与采购市场信息。
用命令行监控博客与 RSS/Atom 源的更新。
汇总 Codex 或 Claude 按模型计费的使用成本。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。