app-platform-sandbox

You can isolate AI agent code execution by creating a sandbox environment that securely runs untrusted code. This Skill provides isolated sandboxes specifically designed to safely execute and test AI agent workflows without risking the host system.

Sandbox hot-pool configuration maintains pre-warmed isolated environments to enable rapid, stateful execution for AI agents. You need hot pools when your testing and iteration workflows demand low-latency sandbox creation and immediate code execution.

Yes, the isolated sandbox supports port exposure and service-mode streaming for AI agents. This allows you to run stateful sessions, stream outputs directly from the sandbox, and integrate live services during testing.

Sandbox management supports filesystem operations and hibernation to control stateful sessions. You can manipulate files within the isolated environment and hibernate active sandboxes to pause execution and conserve resources during testing.

Yes, the sandbox environment provides easy integration with troubleshooting and designer workflows for end-to-end agent development. You can connect isolated testing sessions directly to your existing AI agent design and debugging processes.

While isolated sandboxes provide secure execution for untrusted AI agent code, they require active management via SandboxManager. You must manually handle sandbox creation, configure hot pools, and delete environments when finished to avoid resource accumulation.