arbigent

# Arbigent(Arbiter-Agent): An AI Agent Testing Framework for Modern Applications
<img width="2668" height="1132" alt="arbigent-banner-optimized" src="https://github.com/user-attachments/assets/546c36ed-45fe-4ac2-a918-c7b0e7261f41" />


**Zero to AI agent testing in minutes. Arbigent's intuitive UI and powerful code interface make it accessible to everyone, while its scenario breakdown feature ensures scalability for even the most complex tasks.**

> [!WARNING]
> There seems to be a spam account posing as Arbigent, but the account is not related to me. The creator's accounts are [`https://x.com/_takahirom_`](https://x.com/_takahirom_) and [`https://x.com/new_runnable`](https://x.com/new_runnable) .

## Screenshot

<img width="650" alt="arbigent-screenshot" src="https://github.com/user-attachments/assets/77ebfcb1-3a44-4eaf-9775-3dff2597f9d1" />

## Demo movie

https://github.com/user-attachments/assets/ec582760-5d6a-4ee3-8067-87cb2b673c8d

## Motivation

### Make AI Agent Testing Practical for Modern Applications

Traditional UI testing often relies on brittle methods that are easily disrupted by even minor UI changes. A/B tests, updated tutorials, unexpected dialogs, dynamic advertising, or ever-changing user-generated content can cause tests to fail.  
AI agents emerged as a solution, but testing with AI agents also presents challenges. AI agents often don't work as intended; for example, the agents might open other apps or click on the wrong button due to the complexity of the task.  
To address these challenges, I created Arbigent, an AI agent testing framework that can break down complex tasks into smaller, dependent scenarios. By decomposing tasks, Arbigent enables more predictable and scalable testing of AI agents in modern applications.

### Customizable for Various AI Providers, OSes, Form Factors, etc.

I believe many AI Agent testing frameworks will emerge in the future. However, widespread adoption might be delayed due to limitations in customization. For