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Independent project, not affiliated with Anthropic
epinvest516-web avatar

Mt5 Trading

epinvest516-web/openclaw-skills
293 installs
Summary

This is a full-featured algorithmic trading bot for MetaTrader 5 that trades gold and silver on Windows. The V6.6 "Predator" version implements infinite risk-reward trailing (moving to breakeven at 2R, then following M15 bars), a self-evolution system that blacklists low-performing time slots based on trade journal analysis, and a triple-resonance filter requiring H4 trend, M15 signal, and MACD alignment before entry. It logs everything to CSV for post-mortem review and sends Telegram notifications. You'll need a Windows VPS, MT5 installed, and comfort with running Python trading bots 24/7. The naming is colorful but the architecture is solid for systematic traders who want automated position management with adaptive filtering.

Install to Claude Code

npx -y skills add epinvest516-web/openclaw-skills --skill mt5-trading --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

MT5 Trading System Management (Babata V6.6 Predator Edition)

This skill consolidates the highest-level quant logic for Gold/Silver trading on Windows VPS.

🚀 V6.6 Core Features (The Predator)

1. 🚀 Infinite RR Logic (Smart Trailing)

  • Phase 1 (Breakeven): Move SL to Entry + buffer once Profit >= 2.0 * Initial Risk.
  • Phase 2 (Moon Run): Remove fixed TP. Trail SL behind the previous M15 bar's low/high.
  • Goal: Capture 1:10+ outliers while securing 0-loss trades early.

2. 🧠 Self-Evolution (Blacklist System)

  • Review: Weekly automated analysis of journal.csv.
  • Action: Identifies low-win-rate time/day clusters and generates blacklist.json.
  • Filtering: Automatically skips entry during blacklisted intervals.

3. 🌪️ Triple-Resonance Selector

Entries require 3 layers of alignment:

  • H4 Macro Trend (EMA200 / Structure).
  • M15 Micro Signal (SMC, NakedK, Turtle, Vegas).
  • MACD Momentum (Histogram direction).

4. 📊 Blackbox Data Logging

Full technical context for every trade is stored in journal.csv for post-mortem analysis.

🛠️ Deployment Checklist

  1. Environment: pip install MetaTrader5 pandas requests pytz.
  2. Files: main.py, config.py, engine/, strategies/.
  3. Supervisor: Always run via START_BOT.cmd to ensure auto-restart.
  4. Sync: Commit and push to Github repository for version control.

🔍 Verification

  • Telegram: Confirm receipt of "🐺 Babata V6.6 Predator Active!" message.
  • Journal: Ensure journal.csv is being populated after the first trade.
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Categories
Backend & APIsRelease ManagementAutomation & WorkflowsPythonFinance & Trading
First SeenJun 3, 2026
View on GitHub

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