Reflex – A Discipline Assistant for Prop Firm Traders

Reflex is a local-first desktop application that helps funded traders improve discipline through journaling, gamification, and real-time behavioral feedback. Built using Electron and React, the app provides structured journaling, AI insights, streak tracking, and a floating mascot that responds to the trader’s actions.

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Project Purpose

Traders in prop firm environments (Apex, Topstep, MyFundedFutures, etc.) often fail not because of poor strategy, but because of broken discipline. Reflex addresses this by:

• Encouraging good habits and no-trade days
• Logging every trade with purpose, structure, and review
• Providing real-time feedback through a mascot assistant
• Helping traders stick to their rules and build confidence

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Key Features

• Trade journaling with R:R, grades, notes, and screenshots
• GPT-powered feedback on trade quality and behavioral patterns
• Daily check-ins with streak rewards, XP, and badges
• Rule system with live monitoring (max trades, trading hours, etc.)
• Transparent animated mascot overlay with voice and animation
• Exportable “Discipline Resume” PDF based on behavior, not PnL

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Tech Stack

• Electron – Cross-platform desktop shell
• React + Tailwind CSS – UI framework
• Zustand – Global state management
• SQLite – Local database for journals and progress
• OpenAI GPT-4 – AI feedback and trade analysis
• Lottie – Animated mascot overlay
• Web Audio API – Sound effects and voice

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Project Roadmap

Track progress: Reflex GitHub Project Board

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File Structure Overview

• src/ – Source code (Electron, React, Overlay, Zustand, DB)
• docs/ – Full SDLC documentation (Phases 01–11)
• demo/ – Screenshots and demo video assets
• .github/ – Templates and contribution files
• README.md – Public project overview

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Installation (Coming Soon)

This project is in active development. The MVP scaffold will follow this setup:

1. Clone this repository
   git clone https://github.com/garrettm19/reflex.git

2. Navigate into the project directory
   cd reflex

3. Install dependencies
   npm install

4. Start the development server
   npm run dev

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Getting Started (Planned)

Upon first launch:

1. User is prompted to define rules and settings.
2. Each day begins with a check-in: “Did you trade today?”
3. User logs a trade or a no-trade day.
4. Mascot responds to behavior and feedback is generated via GPT.
5. XP and streaks update automatically.

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Demo

Demo video coming soon. It will include:

• Logging a trade with screenshot and notes
• Receiving GPT feedback
• Mascot reacting to a rule break
• Viewing a 7-day streak and exporting the resume

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Screenshots (To Be Added)

Store the following images in the /demo folder:

• dashboard_screenshot.png
• journal_entry_screenshot.png
• mascot_warning.png
• export_resume.png

Update the table below once available.

Dashboard	Journal Entry	Mascot Warning	Resume Export
(screenshot)	(screenshot)	(screenshot)	(screenshot)

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Full Documentation

This project follows a full software development lifecycle (SDLC). Each phase is documented in /docs/.

• 01 – Problem Discovery
• 02 – Feature Requirements
• 03 – System Architecture
• 04 – Data Model
• 05 – Wireframes
• 06 – AI Design
• 07 – Build Plan
• 08 – Demo and Reflection
• 09 – User Stories
• 10 – Metrics & Success Plan
• 11 – User Persona & Flow

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Next Steps

• Scaffold Electron + React with overlay window
• Add mascot idle and feedback animations
• Implement SQLite journaling backend
• Add XP and badge logic
• Connect GPT feedback to journal entries
• Build resume export functionality
• Add demo screenshots to /demo folder
• Record and upload demo walkthrough video

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License

MIT License

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Author

Built by Mason Garrett
Contact: mgarrett620@gmail.com
GitHub: garrettm19