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GGwujun
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shadow-account

Extract trading rules from journals and backtest them across markets.

Updated Jun 12, 2026
Search Tags:#backtesting#attribution#pdf-report#multi-market#rule-extraction#trade-journal#shadow-account
One-click install
npx skills add https://github.com/GGwujun/SigmX --skill shadow-account-ggwujun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: shadow-account
Source: https://github.com/GGwujun/SigmX/tree/main/agent/src/skills/shadow-account
Command: npx skills add https://github.com/GGwujun/SigmX --skill shadow-account-ggwujun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Shadow Account extracts 3-5 human-readable rules from a user's trade journal to reveal the underlying profitable patterns, then performs cross-market backtesting and attribution to identify where gains came from.

Core Features & Use Cases

  • Rule extraction: derive 3-5 concise trading rules from uploaded journals, with per-rule coverage and holding period insights.
  • Cross-market backtesting: run simulations across China A/HK/US/crypto markets to compare rule performance.
  • Attribution & reporting: produce delta PnL attribution and a structured 8-section PDF/HTML report for review.
  • Narrative shadowing: present a risk-controlled, emotion-free perspective of the trader's strategy.

Quick Start

Upload your trade journal, run the shadow-account workflow, and obtain a 3-5 rule extraction plus a cross-market backtest report in PDF.

Frequently Asked Questions about shadow-account

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

FAQPage Schema
How do I extract actionable trading rules from my trade journal?▼

To extract trading rules from your trade journal, upload it to an automated workflow that analyzes historical data to derive 3-5 concise rules with coverage and holding period insights.

Can I backtest trading rules across multiple markets like China A, HK, US, and crypto?▼

Yes, cross-market backtesting supports China A, HK, US, and crypto markets to simulate extracted rules, providing delta PnL attribution to identify where gains originated.

Does this backtesting tool generate a PDF report for trade journal analysis?▼

Yes, the rendering tool produces an 8-section PDF or HTML report covering rule extraction, multi-market backtesting results, and performance attribution for review.

What do I need to run multi-market backtesting on my trade journal?▼

You need a structured trade journal uploaded to the workflow, which the backtester uses to run cross-market simulations and generate a risk-controlled shadow of your strategy.

What is performance attribution in trade journal backtesting?▼

Performance attribution in backtesting identifies which extracted rules generated gains across different markets, providing a delta PnL breakdown for each rule.

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