👻 Haunted Code Reviewer: Building an AI Code Reviewer with a Ghostly Twist | Hacktoberfest 2026

This is a submission for the "Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine" ( https://dev.to/challenges/hacktoberfest-week4-2026-10-26 )

👻 Haunted Code Reviewer is an AI-powered code review web app that gives developers spooky but useful feedback.

Users paste a code snippet, select a programming language, and summon a ghostly reviewer that identifies potential bugs, logic errors, unused variables, and code improvements.

Inspired by the "Ghost in the Machine" theme, I gave the AI a hidden system prompt that makes it act like a ghost trapped inside a computer while still delivering accurate, beginner-friendly code reviews.

[Try Haunted Code Reviewer – https://haunted-code-reviewer.streamlit.app/ ]

[GitHub Repository– https://github.com/srushtikaware/Haunted-Code-Reviewer ]

I built the app using Python and Streamlit, with the Hugging Face Inference API connecting it to the open-weight Llama 3.1 8B Instruct model.

I developed and deployed the project entirely from my phone using GitHub Codespaces, GitHub, and Streamlit Community Cloud.

Open innovation made this project possible without expensive hardware or proprietary AI infrastructure.

Using an open-weight model through Hugging Face allowed me to experiment with AI-powered code review using accessible tools. Open-source frameworks like Streamlit made it easy to build and share the application.

This project showed me how open tools can lower barriers to development and help beginners participate in AI innovation.

Building this project entirely from my phone was a challenge of its own. From debugging indentation errors to troubleshooting cloud deployment, every obstacle taught me something new.

The most exciting moment was seeing my own AI-powered app open in a browser after working through those challenges. It reminded me that creativity and persistence matter more than having expensive equipment.