AI Coding Sandbox Receipt for Command-Level Delivery Evidence

Direct answer

An AI coding sandbox receipt is a client-readable evidence record for an AI-assisted coding run. It should summarize command classes, changed files, policy exceptions, test proof, and the final delivery scope without exposing raw secrets or unnecessary internal transcript noise.

Where it fits

• A consultant wants to show a client exactly what an AI coding session touched before handing off the patch.
• A team needs evidence that package installs, network requests, writes, tests, and deploy commands were reviewed.
• A regulated engineering group needs a reusable receipt format that is easier to inspect than a raw terminal log.

Operational steps

1. Upload the terminal transcript, AI session summary, and git diff.
2. Classify commands into install, network, write, test, deploy, and secret touch groups.
3. Attach risk labels, test outcomes, coverage or lint proof, and policy exceptions.
4. Generate an HTML or PDF receipt with redaction and retention rules applied.

Common risks

• Raw transcripts may include secrets, local paths, or irrelevant setup noise.
• A receipt that only lists commands without risk context is hard for clients to trust.
• Test results can be misleading when they are not tied to the commands that produced them.

How SandboxReceipt AI helps

SandboxReceipt AI turns uploaded transcripts and diffs into command receipts with classifier output, policy exceptions, test proof, and retention controls.