Hey Devs 👋,
I recently built a fun and insightful game called Chess IQ Analyzer — a project that combines chess, performance analytics, and a touch of psychology. The best part? I built it with a lot of help from Amazon Q CLI, an AI-powered terminal assistant that accelerated the entire process.
Let’s dive into what this project is all about, how I made it, and how you can build something similar too.
🧠 What Is Chess IQ Analyzer?
Chess IQ Analyzer is more than just a chess game. It’s a full-featured chess experience with performance tracking and IQ evaluation based on your moves.
Key Features:
♟️ Play 10-minute games vs a computer powered by the Minimax algorithm
📊 Get post-game stats like accuracy, win/loss ratio, and IQ score
📈 View a chart of your IQ growth over time
🧬 Automatically classify player levels: Beginner, Intermediate, or Master
Think of it like your personal chess coach and analyst — all built in Python using Pygame.
🚀 Tech Stack
Here's the full stack I used:
Feature Tools -> Libraries
Game UI -> pygame
AI Opponent -> Minimax algorithm
Stats & IQ Tracking -> Python logic + JSON
Performance Charts -> matplotlib (for future version)
File Handling -> Standard Python I/O
AI Assistant -> 🧠 Amazon Q CLI
Version Control -> GitHub Desktop
🛠️ How Amazon Q CLI Helped
Before we dive into code — a quick shoutout to Amazon Q CLI 🧠.
Amazon Q CLI is like having an AI-powered coding buddy inside your terminal. I used it to:
Scaffold my folder structure and modules quickly
Generate boilerplate for Python classes (like the Minimax AI logic)
Write testable components
Fix bugs and validate logic inline
👉 If you're building Python games or AI-based apps, Amazon Q CLI can seriously boost productivity while keeping your flow uninterrupted.
🗂️ Project Structure
CHESS_IQ_ANALYZE/
├── assets/ # Chess piece images
├── data/ # Game logs, stats, IQ records
├── chess_engine/ # Game logic and Minimax AI
├── analysis/ # Accuracy & IQ computation
├── iq/ # IQ model & progress tracker
├── ui/ # Pygame board + stats screen
├── utils/ # Configs, logging, file I/O
├── tests/ # Unit tests
├── main.py # Game launcher
├── requirements.txt
├── README.md
👨💻 How It Works
🎮 1. Player vs AI
Start the game and play a 10-minute timed match against a computer opponent powered by the Minimax algorithm. The AI gets smarter as your level increases, giving you a real challenge every time you play.
📥 2. Tracking Moves
Every move you and the AI make is stored in a file called moves_input.json. After each match, this data is automatically logged and used for performance review.
📊 3. Evaluating Performance
Using smart logic in analyzer.py and iq_model.py, the system analyzes your performance and assigns an IQ score based on:
Move accuracy
Game result
Time usage
Decision quality
This IQ is then used to track your chess intelligence growth over time.
🧾 4. Updating Stats
After each game, key statistics are saved in player_stats.json,
including:
🕹️ Total games played
✅ Win/Loss ratio
🧠 Current IQ score
📈 IQ trend line
🧬 Player level: Beginner, Intermediate, or Master
📉 5. Visualization & Reports
We're working on beautiful graph-based IQ visualizations using matplotlib and dynamic dashboards that will let you:
📈 See how your IQ has evolved after each match
🧾 Access a summary report of your stats, accuracy, and progress
🧠 Reflect on how you're improving — not just in chess, but in decision-making too!
These insights will be displayed in the UI via the stats_view.py module.
✨ Final Thoughts
Building this project was not just technically fun — it was creatively rewarding. Using Amazon Q CLI made it even smoother and more enjoyable. Whether you're a beginner or an advanced dev, Q CLI can help you code faster, cleaner, and smarter.
🧠 Play chess. Track your brain. Level up.
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Top comments (1)
interesting, would be great to see the game screenshots or code repo