sandbox-sdk

GitHub

提供 Cloudflare Sandbox SDK 开发指南,涵盖安全代码执行环境的构建、配置及核心 API 使用。适用于 AI 代码解释器、CI/CD 系统及不受信任代码的隔离执行场景。

skills/cloudflare_skills/sandbox-sdk/SKILL.md sediman-agent/OpenSkynet

Trigger Scenarios

构建沙箱化应用 实现代码解释器 在 Workers 上执行不安全代码 配置 Cloudflare 容器环境

Install

npx skills add sediman-agent/OpenSkynet --skill sandbox-sdk -g -y
More Options

Non-standard path

npx skills add https://github.com/sediman-agent/OpenSkynet/tree/main/skills/cloudflare_skills/sandbox-sdk -g -y

Use without installing

npx skills use sediman-agent/OpenSkynet@sandbox-sdk

指定 Agent (Claude Code)

npx skills add sediman-agent/OpenSkynet --skill sandbox-sdk -a claude-code -g -y

安装 repo 全部 skill

npx skills add sediman-agent/OpenSkynet --all -g -y

预览 repo 内 skill

npx skills add sediman-agent/OpenSkynet --list

SKILL.md

Frontmatter
{
    "name": "sandbox-sdk",
    "description": "Build sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI\/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge."
}

Cloudflare Sandbox SDK

Build secure, isolated code execution environments on Cloudflare Workers.

FIRST: Verify Installation

npm install @cloudflare/sandbox
docker info  # Must succeed - Docker required for local dev

Retrieval Sources

Your knowledge of the Sandbox SDK may be outdated. Prefer retrieval over pre-training for any Sandbox SDK task.

Resource URL
Docs https://developers.cloudflare.com/sandbox/
API Reference https://developers.cloudflare.com/sandbox/api/
Examples https://github.com/cloudflare/sandbox-sdk/tree/main/examples
Get Started https://developers.cloudflare.com/sandbox/get-started/

When implementing features, fetch the relevant doc page or example first.

Required Configuration

wrangler.jsonc (exact - do not modify structure):

{
  "containers": [{
    "class_name": "Sandbox",
    "image": "./Dockerfile",
    "instance_type": "lite",
    "max_instances": 1
  }],
  "durable_objects": {
    "bindings": [{ "class_name": "Sandbox", "name": "Sandbox" }]
  },
  "migrations": [{ "new_sqlite_classes": ["Sandbox"], "tag": "v1" }]
}

Worker entry - must re-export Sandbox class:

import { getSandbox } from '@cloudflare/sandbox';
export { Sandbox } from '@cloudflare/sandbox';  // Required export

Quick Reference

Task Method
Get sandbox getSandbox(env.Sandbox, 'user-123')
Run command await sandbox.exec('python script.py')
Run code (interpreter) await sandbox.runCode(code, { language: 'python' })
Write file await sandbox.writeFile('/workspace/app.py', content)
Read file await sandbox.readFile('/workspace/app.py')
Create directory await sandbox.mkdir('/workspace/src', { recursive: true })
List files await sandbox.listFiles('/workspace')
Expose port await sandbox.exposePort(8080)
Destroy await sandbox.destroy()

Core Patterns

Execute Commands

const sandbox = getSandbox(env.Sandbox, 'user-123');
const result = await sandbox.exec('python --version');
// result: { stdout, stderr, exitCode, success }

Code Interpreter (Recommended for AI)

Use runCode() for executing LLM-generated code with rich outputs:

const ctx = await sandbox.createCodeContext({ language: 'python' });

await sandbox.runCode('import pandas as pd; data = [1,2,3]', { context: ctx });
const result = await sandbox.runCode('sum(data)', { context: ctx });
// result.results[0].text = "6"

Languages: python, javascript, typescript

State persists within context. Create explicit contexts for production.

File Operations

await sandbox.mkdir('/workspace/project', { recursive: true });
await sandbox.writeFile('/workspace/project/main.py', code);
const file = await sandbox.readFile('/workspace/project/main.py');
const files = await sandbox.listFiles('/workspace/project');

When to Use What

Need Use Why
Shell commands, scripts exec() Direct control, streaming
LLM-generated code runCode() Rich outputs, state persistence
Build/test pipelines exec() Exit codes, stderr capture
Data analysis runCode() Charts, tables, pandas

Extending the Dockerfile

Base image (docker.io/cloudflare/sandbox:0.7.0) includes Python 3.11, Node.js 20, and common tools.

Add dependencies by extending the Dockerfile:

FROM docker.io/cloudflare/sandbox:0.7.0

# Python packages
RUN pip install requests beautifulsoup4

# Node packages (global)
RUN npm install -g typescript

# System packages
RUN apt-get update && apt-get install -y ffmpeg && rm -rf /var/lib/apt/lists/*

EXPOSE 8080  # Required for local dev port exposure

Keep images lean - affects cold start time.

Preview URLs (Port Exposure)

Expose HTTP services running in sandboxes:

const { url } = await sandbox.exposePort(8080);
// Returns preview URL for the service

Production requirement: Preview URLs need a custom domain with wildcard DNS (*.yourdomain.com). The .workers.dev domain does not support preview URL subdomains.

See: https://developers.cloudflare.com/sandbox/guides/expose-services/

OpenAI Agents SDK Integration

The SDK provides helpers for OpenAI Agents at @cloudflare/sandbox/openai:

import { Shell, Editor } from '@cloudflare/sandbox/openai';

See examples/openai-agents for complete integration pattern.

Sandbox Lifecycle

  • getSandbox() returns immediately - container starts lazily on first operation
  • Containers sleep after 10 minutes of inactivity (configurable via sleepAfter)
  • Use destroy() to immediately free resources
  • Same sandboxId always returns same sandbox instance

Anti-Patterns

  • Don't use internal clients (CommandClient, FileClient) - use sandbox.* methods
  • Don't skip the Sandbox export - Worker won't deploy without export { Sandbox }
  • Don't hardcode sandbox IDs for multi-user - use user/session identifiers
  • Don't forget cleanup - call destroy() for temporary sandboxes

Detailed References

Version History

  • c9d8953 Current 2026-07-05 19:51

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