AI-Hallucination-Detector-for-Code

Anupam hegde — Sun, 08 Feb 2026 16:11:24 +0000

This is a submission for the GitHub Copilot CLI Challenge

What I Built

I built AI Hallucination Detector for Code, a command-line tool that detects hallucinations in AI-generated Python code using static analysis.

The tool identifies:

Hallucinated or fake APIs (non-existent imports)
Logical inconsistencies such as misleading time-complexity claims
Produces a clear hallucination risk score to help developers judge reliability

This project matters to me because AI-assisted coding is becoming mainstream, but correctness and trust remain critical. Instead of generating more code, this project focuses on verifying AI-generated code responsibly.

Demo

🔗 GitHub Repository:

https://github.com/anupam-hegde/AI-Hallucination-Detector-for-Code

🎥 Demo GIF / Video:

(Attached in the repository README)

Demo Flow:

A Python file with a fake import and nested loops is analyzed
The CLI detects:
- API hallucinations
- Logic hallucinations
A risk score is generated with a clean, readable CLI output

The demo shows the tool working end-to-end using a single CLI command.

My Experience with GitHub Copilot CLI

GitHub Copilot CLI played a key role as a development and reasoning assistant throughout this project.

I used Copilot CLI to:

Understand and implement AST-based static analysis
Design safe logic for validating Python imports without executing code
Debug CLI architecture issues related to Typer
Reason about algorithmic complexity and scoring strategies

Copilot helped me move faster and think more clearly, but it was never treated as a source of truth.

All suggestions were manually reviewed and validated using deterministic static analysis — which directly aligns with the goal of this project.

This experience reinforced how Copilot CLI can be a powerful productivity tool when used responsibly and thoughtfully.

Forem: Anupam hegde

AI-Hallucination-Detector-for-Code

What I Built

Demo

My Experience with GitHub Copilot CLI