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Reached 440+ stars! Built an auditable sandbox that records what AI coding agents actually did (self.SideProject)<br>submitted 4 minutes ago by OkBreath9382

AI coding agents are useful, but I still do not fully trust the workflow.

Claude, Codex, Cursor, and other agents can make real changes to a repo: edit files, run shell commands, read logs, access networks, retry failed tests, and produce a final patch. But when I review the result, Git mostly tells me what changed, not what actually happened.

I wanted a way to answer questions like:

what prompt produced this change?

what commands did the agent run?

what logs did it see?

which files did it touch?

what policy or sandbox was applied?

which attempts failed before this patch?

why should I trust this result?

So I built h5i, pronounced “high-five”: an auditable sandbox for AI coding agents.

h5i gives every agent a sandboxed Git worktree and records the prompts, commands, logs, policies, context, and reviews behind every change. The evidence lives in your repo, carried by Git refs, with no SaaS required.

The basic idea is that an AI-generated patch should not just be a diff. It should come with provenance: the prompt, the execution trace, the logs, the review trail, and the environment it ran in.

You can use h5i with one agent as a safer, auditable workspace. Or you can scale it to many agents: give Claude, Codex, or other coding agents separate sandboxed worktrees, let them try different approaches without stepping on each other, then compare the...