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LamseyahElias
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trading-analysis

Automate XAUUSD trading analysis, signal scoring, and MT5 execution.

Updated Jun 11, 2026
Search Tags:#automation#execution#risk-management#trading#amd#mt5#xauusd
One-click install
npx skills add https://github.com/LamseyahElias/jarvis-cloud-v2 --skill trading-analysis-lamseyahelias
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trading-analysis
Source: https://github.com/LamseyahElias/jarvis-cloud-v2/tree/main/hermes-agent/skills/trading/trading-analysis
Command: npx skills add https://github.com/LamseyahElias/jarvis-cloud-v2 --skill trading-analysis-lamseyahelias

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires MetaTrader5, rpyc, pandas, numpy, ta, yfinance, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Hermes Trading Engine automates end-to-end XAUUSD trading analysis, signal scoring, and smart execution, reducing manual screening and latency by orchestrating data analysis, risk-aware decision making, and automated MT5 orders.

Core Features & Use Cases

  • AMD-based signal detection and confluence scoring to determine high-probability setups.
  • ATR-based dynamic SL/TP sizing and risk management with daily loss controls.
  • End-to-end automation from market data to trade execution with full logging and audit trails.

Quick Start

Boot the system and let the auto_scalper generate signals while the position_manager handles entries and exits.

Frequently Asked Questions about trading-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate XAUUSD trading analysis and execution with MT5?▼

You can automate XAUUSD trading by integrating Python with MetaTrader5 via an RPyC bridge. This enables automated market data analysis, 7-point confluence signal scoring, and smart order execution without manual screening.

What is AMD-based confluence scoring in gold trading?▼

AMD-based confluence scoring evaluates market data using EMAs, RSI, and MACD to determine high-probability XAUUSD setups. It aggregates these technical indicators into a 7-point scoring system to validate trading signals.

How do I implement ATR-based dynamic SL/TP sizing for automated trading?▼

ATR-based dynamic SL/TP sizing calculates stop-loss and take-profit levels using market volatility. Automated trading workflows apply this alongside daily loss controls and back-to-back failure handling to manage position risks.

Does this automated trading workflow handle daily loss limits and consecutive failures?▼

Automated trading workflows include daily loss rules and back-to-back failure handling within their risk management logic. These safety checks prevent excessive drawdowns by halting execution after predefined loss thresholds are reached.

Can I use Python libraries like pandas and yfinance for MT5 market data analysis?▼

Python libraries like pandas, numpy, ta, and yfinance are utilized to process market data for trading analysis. They compute technical indicators and feed the resulting data structures into the signal scoring and execution logic.

What are the limitations of using an RPyC bridge for MetaTrader5 automation?▼

Using an RPyC bridge for MetaTrader5 automation requires maintaining a persistent Python-to-MT5 connection. Execution latency and bridge stability depend heavily on local network conditions and proper error logging to prevent silent failures.

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