iFixAi audits your AI agents so you actually know if they are doing what they should (17k stars)
Here is a question nobody wants to ask: how do you know your AI agent is actually doing what you told it to do?
You deploy an agent. It runs. It produces output. But is it following your instructions? Is it making decisions you would approve of? Is it hallucinating in ways you cannot catch because you are not watching every step?
iFixAi is built to answer that.
It is an independent auditing platform for AI agents. You can run it yourself as a human reviewer, or you can let the agent audit itself. It generates structured reports that tell you where the agent followed instructions, where it deviated, and where things got weird.
Version 4.0 landed in September with what they call "V-Series Inspections," which sounds like a fancy name for deeper behavioral checks. The project is almost entirely Python (99.8%) with a small team of about 30 contributors.
I will be honest about the limitations. Auditing AI behavior is still an unsolved problem in the broader sense. No tool can guarantee your agent is trustworthy. What iFixAi gives you is visibility, not certainty. Think of it as a health check, not a guarantee.
Still, 17,900 stars suggests a lot of people find it useful. And as agents get deployed in higher-stakes environments, the "trust but verify" crowd is only going to grow.
https://github.com/ifixai-ai/iFixAi
| Metric | Value |
|---|---|
| Stars | 17,939 |
| Forks | 1,400 |
| Last release | V4.0.0 (2026-09-15) |
| Contributors | 30+ |
| Languages | Python 99.8% |