Mt5 Trading
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 copies · 90 days. Times the install command was copied on this site in the last 90 days, bots filtered.
- 12
- skills.sh installs
- 323
- last updated
- Aug 21, 2026
Install
$ npx -y skills add epinvest516-web/openclaw-skills --skill mt5-trading --agent claude-codeInstalls into .claude/skills of the current project.
Files
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.
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- Repository
- github.com/epinvest516-web/openclaw-skills
- Categories
- Backend & APIs, Release Management, Automation & Workflows, Python, Finance & Trading
- First seen
- Jun 3, 2026
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