I built Kule: AI agents work on a copy of your folder, and you decide what comes back

说明与用途

Kule 让 AI 代理在文件夹副本上工作，审核并批准更改后再应用到真实文件系统，提供沙箱和基于策略的控制。

问题

Coding agents run commands as the user, exposing sensitive files, keys, and network access; users cannot see the actual effects of commands before approval, leading to accidental or malicious changes.

结果

Kule enables safe, reviewable AI agent interactions with local folders, preventing accidental or malicious changes by isolating agent actions and requiring policy‑based approval before committing.

工作流

• Create a task with kule new <folder>
• Run an agent or command with kule exec or kule run
• Review the list of changes and policy verdicts with kule status or kule steps
• Commit approved changes with kule commit or undo with kule undo

证据

Kule gives it a copy‑on‑write copy of that folder inside a sandbox, looks at what every command really changed, and lets nothing reach the real folder until a policy, or you, says so.

来源

Every command runs in the OS sandbox: Seatbelt on macOS, Landlock + seccomp + namespaces on Linux. It can write only to the copy and its own temp folders.

来源

With the default ("balanced") policy: ordinary edits pass; manifests and lockfiles wait for approval; git hooks are denied.

来源

Two tasks can work on the same folder. A file both of them changed merges method by method, and only the parts that were changed twice conflict.

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