This is a submission for the GitHub Copilot CLI Challenge
What I Built
I built Q-Drift CLI, a quantum-inspired structural drift analyzer. It simulates probabilistic “qubit-like” states to detect instability in logic or decision systems.
The CLI runs thousands of simulations under adjustable “noise” levels and reports entropy, collapse bias, and a visual ASCII graph showing the distribution of outcomes. This tool makes abstract quantum-inspired concepts tangible and fun, all within the terminal.
It’s designed as a minimal, interactive CLI experience, perfect for developers who want to explore quantum-inspired simulations quickly without heavy setups.
Demo
Above is a sample screenshot showing Q-Drift analyzing a system with 20% noise.
You can also run the CLI yourself with:
python main.py analyze --simulations 1000 --noise 0.2
It outputs a beautiful table, a bar chart of state collapses, and an entropy score indicating stability or fragility.
My Experience with GitHub Copilot CLI
At first, I was completely new to using a CLI and felt a bit intimidated. However, as I started using GitHub Copilot CLI, I became increasingly excited. It guided me through commands, suggested helpful patterns, and made the terminal feel approachable.
As a software engineering student, I usually don’t work extensively in the terminal, but this experience inspired me to dive deeper. The possibilities feel endless, and I now see the CLI as a powerful space for creating quantum-inspired, AI-enhanced tools like Q-Drift. Copilot turned what could have been a daunting experience into an engaging, creative learning journey.
Additional Notes
- This project is open source under the MIT License – free for personal, educational, and commercial use.
- All the outputs in JSON (if enabled) or the visual table are automatically generated, demonstrating quantum-inspired probabilistic simulation.
Top comments (2)
This is fascinating! Quantum-inspired drift detection right in the terminal — such a creative idea. I love how you're blending advanced concepts (quantum) with practical dev tools (CLI). Would love to understand more about the "quantum-inspired" part — is it using actual quantum algorithms or just inspired by the math? Great work on the GitHub Copilot challenge!
Thank you so much! I really appreciate your kind words 😊
Q-Drift is actually quantum-inspired rather than real quantum computing. I'm currently learning and exploring quantum concepts, and this project started as an experiment to see how ideas from quantum thinking, like probabilistic states and evolving systems, could inspire a practical developer tool inside the terminal.
So instead of running quantum algorithms, it uses classical computation while borrowing inspiration from the math and intuition behind quantum systems to detect behavioral drift over time.
I'm still learning and evolving the idea as I go, and that exploration is honestly one of the most exciting parts of building Q-Drift. Really happy you found it interesting!