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trade-journal-analytics

Record trades and compute win rate, SQN, and drawdown metrics.

10|2|Updated Mar 8, 2026
Search Tags:#performance#analytics#reporting#streaks#drawdown#data-persistence#trade-journal
One-click install
npx skills add https://github.com/mahmoud20138/Tradecraft --skill trade-journal-analytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trade-journal-analytics
Source: https://github.com/mahmoud20138/Tradecraft/tree/main/plugins/tradecraft/skills/trade-journal-analytics
Command: npx skills add https://github.com/mahmoud20138/Tradecraft --skill trade-journal-analytics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Handles complete trade journalling and performance analysis—from logging trades to generating publication-ready reports—so traders can understand performance, reduce mistakes, and improve decision-making.

Core Features & Use Cases

  • Trade logging and persistence with structured records
  • Performance analytics, streaks, and drawdown tracking
  • Tag-based drill-down and comprehensive reporting for Prop/ICA

Quick Start

Log your first trade, compute analytics, and generate a summary report in minutes.

Frequently Asked Questions about trade-journal-analytics

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

FAQPage Schema
How do I compute win rate and drawdown from a trade journal?▼

Trade analytics records your trades in a pandas-based data model with a JSON persistence layer, computing aggregated metrics like win rate, SQN, and drawdown to track performance and generate equity curves.

What is the best way to track trading streaks and equity curves?▼

The best way to track trading streaks and equity curves is by logging trades into a structured pandas-based data model, which automatically detects winning and losing streaks while calculating your ongoing equity curve.

How do I generate performance reports for multiple trading instruments?▼

To generate performance reports for multiple trading instruments, log your trades with tags to enable tag-based drill-down, which computes aggregated analytics and produces comprehensive reporting across your entire portfolio.

Does trade journal analytics support data persistence for historical records?▼

Yes, this trade journal analytics approach supports data persistence by utilizing a pandas-based data model with a persistence layer that stores your trades in JSON format for historical recording and analysis.

Can I use pandas for automated trade journaling and performance analysis?▼

Yes, you can use a pandas-based data model for automated trade journaling and performance analysis, which handles everything from logging structured trades to computing metrics and generating publication-ready reports.

What metrics are needed to reduce trading mistakes and improve decision-making?▼

Metrics needed to reduce trading mistakes include win rate, SQN, drawdown, and streak detection, which analyze your trading performance to identify patterns, reduce errors, and improve overall decision-making.

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