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forge-monitor

Poll MT5/MQL5 FORGE EA backtest journals for signals, trades, and anomalies.

Updated Aug 23, 2026
Search Tags:#debugging#monitoring#backtest#mql5#mt5#floating-analysis
One-click install
npx skills add https://github.com/ephico2real2/aurum-signal --skill forge-monitor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: forge-monitor
Source: https://github.com/ephico2real2/aurum-signal/tree/main/.claude/skills/forge-monitor
Command: npx skills add https://github.com/ephico2real2/aurum-signal --skill forge-monitor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill facilitates live monitoring of MT5/MQL5 FORGE EA backtests by continuously polling the source journal database, allowing traders and developers to observe signals, trades, and system behavior in real time for efficient debugging.

Core Features & Use Cases

  • Backtest Oversight: Polls the tester journal database every 45 seconds to provide updated insights into signals, skips, trades, and gate statuses.
  • Anomaly Detection: Flags suspicious patterns such as atr=0, identical prices, unexpected trade counts, or cascade firing issues.
  • Reporting & Documentation: Generates per-run analysis documents and maintains an up-to-date cheat sheet for monitoring queries.
  • Use Case: When debugging complex EA behaviors during a backtest, users can tail the journal to identify anomalies and verify system performance without disrupting the trading environment.

Quick Start

Invoke the skill to start monitoring the forge tester journal and observe updates in real time.

Frequently Asked Questions about forge-monitor

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

FAQPage Schema
How do I monitor MT5 backtests in real time for debugging?▼

MT5 backtest monitoring polls the source journal database every 45 seconds to extract real-time signals, trades, and system anomalies for live debugging. It allows traders to observe EA behavior continuously without disrupting the trading environment.

What kind of anomalies can be detected during MQL5 EA backtesting?▼

MQL5 backtesting anomaly detection flags suspicious patterns such as atr=0, identical prices, unexpected trade counts, and cascade firing issues. It helps developers identify irregular EA behaviors directly from the tester journal database.

Do I need access to the tester journal database to analyze MT5 backtests?▼

Accessing the tester journal database is required for accurate live data analysis of MT5 backtests. The monitoring skill polls this database directly to extract signals, skips, trades, and gate statuses for real-time reporting.

How do I generate reports for MT5 EA backtest runs?▼

Generate MT5 backtest reports by polling the source journal database to create per-run analysis documents. The monitoring process also maintains an up-to-date cheat sheet for querying and documenting system anomalies.

What is the best way to debug unexpected trade counts in MT5 backtesting?▼

Debug unexpected trade counts in MT5 backtesting by tailing the tester journal to identify anomalies and verify system performance. The monitoring skill flags these suspicious patterns automatically during the 45-second polling intervals.

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