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sandbox-sdk

Execute untrusted code and shell commands in isolated Docker-based sandboxes.

Updated Mar 25, 2026
Search Tags:#docker#cloudflare#sandbox#code-interpreter#code-execution#secure-execution#preview-urls
One-click install
npx skills add https://github.com/involvex/skills --skill sandbox-sdk-involvex
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sandbox-sdk
Source: https://github.com/involvex/skills/tree/main/skills/sandbox-sdk
Command: npx skills add https://github.com/involvex/skills --skill sandbox-sdk-involvex

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provide a hardened, isolated runtime for executing untrusted code, commands, and AI-generated scripts without exposing host resources or user data.

Core Features & Use Cases

  • Lifecycle & Management: getSandbox, sleep/keepAlive options, and explicit destroy for resource cleanup.
  • Execution APIs: exec for shell commands and runCode with persistent code contexts for interpreter-style workflows.
  • File & Port Operations: read/write/list files, expose preview URLs for HTTP services, and work with Docker-based container images.
  • Use Case: Run LLM-generated Python analysis in a per-session sandbox, persist state in a code context, and expose a temporary preview URL for web-based results during debugging.

Quick Start

Create a sandbox for user-123, open a Python code context, run sum([1,2,3]) in that context, and return the output.

Frequently Asked Questions about sandbox-sdk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run untrusted code securely in a sandbox without exposing host resources?▼

To run untrusted code securely, use a sandboxed execution environment that isolates commands and file operations via Docker-based container images. This prevents unauthorized access to host resources and user data while executing shell commands and AI-generated scripts.

Can I execute shell commands and maintain persistent code contexts for AI interpreters?▼

Yes, you can execute shell commands using the exec API and maintain persistent code contexts via the runCode API. This supports interpreter-style workflows for AI-generated Python analysis by preserving state across multiple executions within the same session.

How do I expose preview URLs for HTTP services running inside a secure sandbox?▼

You can expose preview URLs by mapping exposed ports from the sandboxed environment to temporary external addresses. This allows you to share web-based results and debug HTTP services running inside the container during the active session.

What is the best way to manage sandbox lifecycle and ensure resource cleanup?▼

Manage sandbox lifecycle by utilizing getSandbox to initialize environments, applying sleep or keepAlive options for persistence, and explicitly calling destroy controls. This ensures proper resource cleanup and prevents orphaned containers after execution.

Does this sandbox execution environment support Cloudflare Workers and durable object bindings?▼

Yes, the sandbox execution environment fully supports Cloudflare Workers development and includes durable object bindings. This allows you to integrate isolated command execution and file operations directly within your Cloudflare infrastructure.

How do I handle file operations like reading and writing files in a code interpreter sandbox?▼

You handle file operations by utilizing the built-in file I/O capabilities to read, write, and list files within the isolated container. This allows LLM-generated scripts to persist outputs and manage data securely during execution.

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