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trade-journal

Analyze trading journal CSV files to generate a trading profile and identify behavioral biases.

1|Updated Jun 23, 2026
Search Tags:#market analysis#behavioral finance#trading analysis#trading journal#trading biases
One-click install
npx skills add https://github.com/644408071-design/Kokpop --skill trade-journal-644408071-design
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trade-journal
Source: https://github.com/644408071-design/Kokpop/tree/main/agent/src/skills/trade-journal
Command: npx skills add https://github.com/644408071-design/Kokpop --skill trade-journal-644408071-design

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill analyzes your trading journal to provide a comprehensive trading profile and identify behavioral biases that may affect your trading performance.

Core Features & Use Cases

  • Trading Profile: Generate a detailed profile of your trading history, including win rate, PnL ratio, and market distribution.
  • Behavior Diagnostics: Identify common trading biases such as disposition effect, overtrading, chasing momentum, and anchoring.
  • Use Case: Upload your trading journal to gain insights into your trading habits and make informed decisions to improve your strategy.

Quick Start

Analyze your trading journal by calling the analyze_trade_journal tool with the file path to your journal, e.g., analyze_trade_journal(file_path="trade-journal.csv").

Frequently Asked Questions about trade-journal

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

FAQPage Schema
How do I analyze my trading journal for behavioral biases?▼

To analyze your trading journal for behavioral biases, you can process your trade history to identify patterns like the disposition effect and overtrading. The tool generates a trading profile detailing win rates and PnL ratios to highlight behavioral biases.

Can I analyze a trading journal exported from Tonghuashun or Futu?▼

You can analyze a trading journal exported from Tonghuashun, Eastmoney, Futu, or generic CSV files. The tool parses these formats directly to calculate market distribution and diagnose behavioral biases from your trading data.

What common trading biases can be identified from a trading journal?▼

Identifying trading biases from a journal includes detecting the disposition effect, overtrading, chasing momentum, and anchoring. The analysis evaluates your trade history to expose these behavioral patterns and their impact on trading performance.

Does trading journal analysis require Python libraries like pandas and numpy?▼

Trading journal analysis requires Python libraries like pandas, numpy, and scipy for data processing. These dependencies handle the statistical computations needed to generate your trading profile and diagnose behavioral biases.

How do I run a trading profile analysis on a CSV file?▼

To run a trading profile analysis on a CSV file, execute the analysis tool with your file path. It processes the trade records to generate a comprehensive profile including win rate, PnL ratio, and market distribution.

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