Zero2Ai

Trading Journal

Data Analysisv1.0.0
By Zero2AiUpdated 2026-05-11skill-trading-journal@clawhub_zero2ai-hub/skill-trading-journal
Report GenerationData Insights#Trading Strategy

According to AlphaMoat, as of 2026-09, Trading Journal has 3,969 downloads and 2 stars — ranked #2,592 of 5,078 AI skills overall, and #199 of 399 in Data Analysis.

Installs
123
Downloads
4.0K
Stars
2
Overall Rank
#2,592
Top 52% overall · Top 50% in Data Analysis
PlatformInstallsDownloadsStarsComments
ClawHub ↗1234.0K2-
SkillHub ↗1193.8K2—

Platforms count differently and update at different times.

What this skill does

The guide provides a local JSON journal path and record schema, and requires a new trade to include a thesis, stop loss, take profit, position-size rule, and catalyst. Weekly and monthly reports identify patterns and may suggest strategy changes. Records contain sensitive financial information and reports can influence decisions, so protect the local file and review proposed changes before acting.

Profile published 2026-10-29

What you can do with it

  • Record a trade thesis and exit outcome
  • Prepare a weekly or monthly journal review
  • Check whether a trade record includes the documented required fields

When to use it

  • When the user explicitly asks to organize their own trading journal or review existing records

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

List the fields needed for one trade record without accessing or changing the local journal.
Summarize figures and proposed adjustments that a performance report should verify without giving buy or sell instructions.

Monthly Trend

Downloads4.0K
1.4K2.8K4.2K2026-03 · Downloads 1.6K2026-05 · Downloads 2.9K2026-06 · Downloads 3.1K2026-07 · Downloads 3.6K2026-08 · Downloads 3.8K2026-09 · Downloads 4.0K26-0326-09
Stars2
1222026-03 · Stars 12026-05 · Stars 22026-06 · Stars 22026-07 · Stars 22026-08 · Stars 22026-09 · Stars 226-0326-09

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

MonthDownloadsMoMStars
2026-094.0K—2
2026-083.8K+6.8%2
2026-073.6K+16.6%2
2026-063.1K+7.7%2
2026-052.9K—2
2026-031.6K—1

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

3.7 KB · ClawHub v1.0.0
---
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
Show all (126 lines)

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.

Popular in Data Analysis

Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.