AI Trading Journal

v1.0.0

Log every trade with full context (thesis, entry, exit, PnL, emotion, lesson). Generate weekly and monthly performance reports. Identify patterns in wins/los...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for mars82311111/trading-journal-ai.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "AI Trading Journal" (mars82311111/trading-journal-ai) from ClawHub.
Skill page: https://clawhub.ai/mars82311111/trading-journal-ai
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install trading-journal-ai

ClawHub CLI

Package manager switcher

npx clawhub@latest install trading-journal-ai
Security Scan
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Purpose & Capability
Name/description (trade logging, reports, pattern identification) align with the SKILL.md: all instructions focus on recording trades to a local journal and producing summaries. The integrations named (other skills like skill-crypto-threshold-watcher, binance-pro) are plausible collaborators and consistent with a trading-journal skill. One mismatch: registry Owner ID (kn7fqjbnftt52xn0jx866j99hx828z2y) differs from _meta.json ownerId (kn7dj907h1ps8kt92wbdspr01d820vzf); this is an administrative inconsistency worth verifying with the publisher but does not by itself change the functional coherence.
Instruction Scope
Runtime instructions are narrowly scoped: they read/write a local file (~/.openclaw/workspace/trading/journal.json), validate required trade fields, and produce weekly/monthly summaries. The skill does not instruct reading unrelated system files, accessing arbitrary env vars, or exfiltrating data to external endpoints. It references other skills for signals/context — those may introduce additional behaviors, but are outside this skill's instructions.
Install Mechanism
No install spec and no code files — instruction-only. Nothing is downloaded or written by an installer, minimizing supply-chain risk.
Credentials
Requires no environment variables, credentials, or config paths. This is proportionate to a local journal skill. Note: connecting this skill to execution or exchange-integration skills (e.g., binance-pro) could cause sensitive credentials to be used by those other skills — review those skills before linking.
Persistence & Privilege
always:false and default model invocation are appropriate. The skill writes/reads a local journal file only; it does not request permanent platform privileges or modify other skills' configurations.
Assessment
This skill appears internally consistent: it stores a local JSON journal and generates reports, and it does not request credentials or install code. Before installing, (1) verify the publisher/owner mismatch in _meta.json vs registry metadata to ensure you trust the source; (2) be aware the journal file (~/.openclaw/workspace/trading/journal.json) will contain sensitive financial data — consider encrypting or restricting file permissions and backing it up securely; (3) review any other skills you plan to connect (binance-pro, skill-crypto-threshold-watcher, backtest-expert) because those may require API keys or external network access and could transmit journal data; and (4) confirm that the agent's access to the filesystem is acceptable for you (the skill expects the agent to write/read the journal file).

Like a lobster shell, security has layers — review code before you run it.

aivk972qjdwh27qmgpk71w7f9377h83yeyffinancevk972qjdwh27qmgpk71w7f9377h83yeyfjournalvk972qjdwh27qmgpk71w7f9377h83yeyflatestvk972qjdwh27qmgpk71w7f9377h83yeyftradingvk972qjdwh27qmgpk71w7f9377h83yeyf
178downloads
0stars
1versions
Updated 3w ago
v1.0.0
MIT-0

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

{
  "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.

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