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Shadow Account Trade Analyzer

Distills your trading journal into plain-language rules, backtests them, and reports the gap versus your real results

Source Download skill
Repository
HKUDS/Vibe-Trading
Stars
37,433
Licence
MIT
Files
1 file

What it does

This skill lets an AI agent take a user's uploaded trading history (a brokerage statement, called a trade journal) and extract 3-5 plain-language rules describing how the user's profitable trades tend to look. It then backtests those rules across China A-shares, Hong Kong, US stocks and crypto, compares the result with what the user actually earned, and explains the difference, such as trades that broke no rule or exits that came too early or too late. It can also produce an 8-section PDF report and list symbols that currently match the rule entry pattern, for research only.

Great for

  • Retail traders who want to see whether their own habits, rather than random noise, drive their profits
  • Analysts reviewing a trader's journal who want a structured backtest and attribution breakdown
  • Developers building trading-review workflows on top of the Vibe-Trading toolset

Skip it if

  • Anyone expecting trading advice or buy signals: the skill says its scan output is research only, and backtests on past trades do not predict future returns
  • Users with fewer than 5 profitable round-trips in their journal: the skill is designed to raise an error rather than invent rules
  • Users who expect the tool to place orders: the skill states it never connects to any order channel

Try asking

  • “Analyse my uploaded trade journal and extract the rules behind my profitable trades”
  • “Backtest my trading style across A-shares, Hong Kong, US stocks and crypto and show the PnL gap”
  • “Render a PDF report explaining how much more I could have earned by following my own rules”
  • “Scan which symbols today fall inside my shadow strategy's entry window, for research only”
Step-by-step guide: how to use Shadow Account Trade AnalyzerInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    shadow-account.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip shadow-account.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip shadow-account.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Review the extracted rules before running the backtest; if they do not sound like you, ask for a higher min_support and rerun
  • Treat the delta PnL and scan results as research observations, not trading instructions
  • Keep your journal file private, since it contains personal financial records

What's inside

  • SKILL.md

Redistributed unmodified from HKUDS/Vibe-Trading under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.