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zeroboot-vm-sandboxZeroboot 虚拟机沙箱

Agent Skill

zeroboot-vm-sandbox 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

23,520

周安装

983

GitHub Stars

39

下载量

8,240
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:zeroboot-vm-sandbox(Zeroboot 虚拟机沙箱)
来源仓库:https://github.com/aradotso/trending-skills
仓库路径:skills/zeroboot-vm-sandbox
安装命令:
npx skills add https://github.com/aradotso/trending-skills --skill zeroboot-vm-sandbox
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/aradotso/trending-skills --skill zeroboot-vm-sandbox

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • zeroboot-vm-sandbox 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Zeroboot VM Sandbox

Skill by ara.so — Daily 2026 Skills collection.

Zeroboot provides sub-millisecond KVM virtual machine sandboxes for AI agents using copy-on-write forking. Each sandbox is a real hardware-isolated VM (via Firecracker + KVM), not a container. A template VM is snapshotted once, then forked in ~0.8ms per execution using mmap(MAP_PRIVATE) CoW semantics.

How It Works

Firecracker snapshot ──► mmap(MAP_PRIVATE) ──► KVM VM + restored CPU state
                           (copy-on-write)          (~0.8ms)
  1. Template: Firecracker boots once, pre-loads your runtime, snapshots memory + CPU state
  2. Fork (~0.8ms): New KVM VM maps snapshot memory as CoW, restores CPU state
  3. Isolation: Each fork is a separate KVM VM with hardware-enforced memory isolation

Installation

Python SDK

pip install zeroboot

Node/TypeScript SDK

npm install @zeroboot/sdk
# or
pnpm add @zeroboot/sdk

Authentication

Set your API key as an environment variable:

export ZEROBOOT_API_KEY="zb_live_your_key_here"

Never hardcode keys in source files.

Quick Start

REST API (cURL)

curl -X POST https://api.zeroboot.dev/v1/exec \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $ZEROBOOT_API_KEY" \
  -d '{"code":"import numpy as np; print(np.random.rand(3))"}'

Python

import os
from zeroboot import Sandbox

# Initialize with API key from environment
sb = Sandbox(os.environ["ZEROBOOT_API_KEY"])

# Run Python code
result = sb.run("print(1 + 1)")
print(result)  # "2"

# Run multi-line code
result = sb.run("""
import numpy as np
arr = np.arange(10)
print(arr.mean())
""")
print(result)

TypeScript / Node.js

import { Sandbox } from "@zeroboot/sdk";

const apiKey = process.env.ZEROBOOT_API_KEY!;
const sb = new Sandbox(apiKey);

// Run JavaScript/Node code
const result = await sb.run("console.log(1 + 1)");
console.log(result); // "2"

// Run async code
const output = await sb.run(`
const data = [1, 2, 3, 4, 5];
const sum = data.reduce((a, b) => a + b, 0);
console.log(sum / data.length);
`);
console.log(output);

Common Patterns

AI Agent Code Execution Loop (Python)

import os
from zeroboot import Sandbox

def execute_agent_code(code: str) -> dict:
    """Execute LLM-generated code in an isolated VM sandbox."""
    sb = Sandbox(os.environ["ZEROBOOT_API_KEY"])
    try:
        result = sb.run(code)
        return {"success": True, "output": result}
    except Exception as e:
        return {"success": False, "error": str(e)}

# Example: running agent-generated code safely
agent_code = """
import json
data = {"agent": "result", "value": 42}
print(json.dumps(data))
"""
response = execute_agent_code(agent_code)
print(response)

Concurrent Sandbox Execution (Python)

import os
import asyncio
from zeroboot import Sandbox

async def run_sandbox(code: str, index: int) -> str:
    sb = Sandbox(os.environ["ZEROBOOT_API_KEY"])
    result = await asyncio.to_thread(sb.run, code)
    return f"[{index}] {result}"

async def run_concurrent(snippets: list[str]):
    tasks = [run_sandbox(code, i) for i, code in enumerate(snippets)]
    results = await asyncio.gather(*tasks)
    return results

# Run 10 sandboxes concurrently
codes = [f"print({i} ** 2)" for i in range(10)]
outputs = asyncio.run(run_concurrent(codes))
for out in outputs:
    print(out)

TypeScript: Agent Tool Integration

import { Sandbox } from "@zeroboot/sdk";

interface ExecutionResult {
  success: boolean;
  output?: string;
  error?: string;
}

async function runInSandbox(code: string): Promise<ExecutionResult> {
  const sb = new Sandbox(process.env.ZEROBOOT_API_KEY!);
  try {
    const output = await sb.run(code);
    return { success: true, output };
  } catch (err) {
    return { success: false, error: String(err) };
  }
}

// Integrate as a tool for an LLM agent
const tool = {
  name: "execute_code",
  description: "Run code in an isolated VM sandbox",
  execute: async ({ code }: { code: string }) => runInSandbox(code),
};

REST API with fetch (TypeScript)

const API_BASE = "https://api.zeroboot.dev/v1";

async function execCode(code: string): Promise<string> {
  const res = await fetch(`${API_BASE}/exec`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${process.env.ZEROBOOT_API_KEY}`,
    },
    body: JSON.stringify({ code }),
  });
  if (!res.ok) {
    const err = await res.text();
    throw new Error(`Zeroboot error ${res.status}: ${err}`);
  }
  const data = await res.json();
  return data.output;
}

Health Check

curl https://api.zeroboot.dev/v1/health

API Reference

POST /v1/exec

Execute code in a fresh sandbox fork.

Request:

{
  "code": "print('hello')"
}

Headers:

Authorization: Bearer <ZEROBOOT_API_KEY>
Content-Type: application/json

Response:

{
  "output": "hello\n",
  "duration_ms": 0.79
}

Performance Characteristics

MetricValue
Spawn latency p50~0.79ms
Spawn latency p99~1.74ms
Memory per sandbox~265KB
Fork + exec Python~8ms
1000 concurrent forks~815ms
  • Each sandbox is a real KVM VM — not a container or process jail
  • Memory isolation is hardware-enforced (not software)
  • CoW means only pages written by your code consume extra RAM

Self-Hosting / Deployment

See docs/DEPLOYMENT.md in the repo. Requirements:

  • Linux host with KVM support (/dev/kvm accessible)
  • Firecracker binary
  • Rust 2021 edition toolchain
# Check KVM availability
ls /dev/kvm

# Clone and build
git clone https://github.com/adammiribyan/zeroboot
cd zeroboot
cargo build --release

Architecture Notes

  • Snapshot layer: Firecracker VM boots once per runtime template, memory + vCPU state saved to disk
  • Fork layer (Rust): mmap(MAP_PRIVATE) on snapshot file → kernel handles CoW page faults per VM
  • Isolation: Each fork has its own KVM VM file descriptors, vCPU, and page table — fully hardware-separated
  • No shared kernel: Unlike containers, each sandbox runs its own kernel instance

Troubleshooting

/dev/kvm not found (self-hosted)

# Enable KVM kernel module
sudo modprobe kvm
sudo modprobe kvm_intel  # or kvm_amd

API returns 401 Unauthorized

  • Verify ZEROBOOT_API_KEY is set and starts with zb_live_
  • Check the key is not expired in your dashboard

Timeout on execution

  • Default execution timeout is enforced server-side
  • Break large computations into smaller chunks
  • Avoid infinite loops or blocking I/O in sandbox code

High memory usage (self-hosted)

  • Each VM fork starts at ~265KB CoW overhead
  • Pages are allocated on write — memory grows with sandbox activity
  • Tune concurrent fork limits based on available RAM

Resources

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.42%
按下载量换算3,083

Claude

29.7%
按下载量换算2,447

Cursor

19.29%
按下载量换算1,589

Gemini CLI

9.93%
按下载量换算818

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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