Original Summary

I've been working on StepFork , an open-source project that helps developers understand what happened during an AI agent run, reproduce failures offline, and generate regression tests. The goal is to make debugging agent workflows more reliable and less dependent on reproducing issues in a live environment. What StepFork supports Record AI agent executions and inspect traces. Replay recorded executions to investigate failures. Fork executions to experiment with fixes. Minimize failing traces to make bugs easier to isolate. Generate regression tests to help prevent bugs from returning. The project has reached v0.2.1 , and I've been working on testing, documentation, and release reliability. I'm now looking to grow the contributor community and make the project useful to more developers. I'm especially looking for contributors interested in: Adding Windows and macOS CI smoke tests. Improving CLI error-handling test coverage. Writing a runnable LangGraph integration tutorial. Expanding trace-redaction regression tests. Improving instrumentation coverage reporting. You don't need to take on a huge feature. Small, focused pull requests and constructive feedback are welcome. The repository has open issues with defined scopes and acceptance criteria, including good first issues. Links GitHub: https://github.com/utsab345/stepfork Open issues: https://github.com/utsab345/stepfork/issues Contributing guidelines: https://github.com/utsab345/stepfork/blob/main/CONTRIBUTING.md I'd appreciate feedback from people building AI agents, working on observability and testing, or maintaining open-source developer tools. What would you want from a tool like this to make debugging AI agent workflows easier?   submitted by   /u/Low-Cut-528 [link]   [comments]

  • 情报分类：开源项目与落地
  • 分类依据：内容涉及项目实践、创业、副业或变现
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/20 14:16:15