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Agent Skill · 效率

multi-env-isolator(多环境隔离器)

multi-env-isolator 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

multi-env-isolator 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 11,015。

总安装 4,823周安装 197GitHub Stars 公开资料未说明下载 1,544核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.0.0

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:multi-env-isolator(多环境隔离器)
来源仓库:https://github.com/rm-huang/multi-env-isolator
安装命令:
openclaw skills install multi-env-isolator
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install multi-env-isolator

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

用于辅助前端页面、组件、样式和交互逻辑开发。适合在 OpenClaw 中维护前端项目、生成组件或检查界面实现。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。

multi-env-isolator 属于效率类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install multi-env-isolator;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

multi-env-isolator 怎么安装?

在终端执行 openclaw skills install multi-env-isolator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

multi-env-isolator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

multi-env-isolator 需要什么权限?

权限级别是接触敏感数据。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。

multi-env-isolator 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

multi-env-isolator 用的人多吗?

公开数据是累计安装 4,823 次,近一周安装 197 次,下载 1,544 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

multi-env-isolator 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
multi-env-isolator

多环境隔离器 · 本页

4,823—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
multi-env-isolator
description
|

Multi-Environment Isolator

Generate isolated dev/test/prod environments for uvicorn/FastAPI projects with frontend support (Vue/React) with one command.

What This Skill Does

This skill solves a common problem in multi-agent AI teams: developers, testers, and production users stepping on each other's toes. It generates a complete environment isolation setup so that:

  • Valina (Developer) can freely break things on ports 8000/3000 without affecting anyone
  • Choco (Tester) can validate releases on ports 8001/3001 with isolated test data and Playwright tests
  • Production stays stable on ports 8002/4173, untouched by dev/test activity

Each environment gets its own config file, startup scripts (backend + frontend), database, media storage, and Playwright test configuration — completely isolated from the others.

What Gets Generated

Running the setup script creates this structure inside the target project:

your-project/
├── .env.dev              # Dev config: DEBUG=True, hot reload, no rate limit
├── .env.test             # Test config: rate limiting enabled, QA settings
├── .env.prod             # Prod config: DEBUG=False, secure CORS, multi-worker
├── scripts/
│   # Backend scripts
│   ├── start-backend-dev.sh    # Starts dev server on port 8000 with --reload
│   ├── start-backend-test.sh   # Starts test server on port 8001
│   └── start-backend-prod.sh   # Starts prod server on port 8002 with auto workers
│   # Frontend scripts (Vue/React)
│   ├── start-frontend-dev.sh   # Starts dev frontend on port 3000
│   ├── start-frontend-test.sh  # Starts test frontend on port 3001
│   └── start-frontend-prod.sh  # Starts prod frontend on port 4173 (preview)
│   # Test scripts
│   └── run-playwright-tests.sh # Runs Playwright E2E tests on test environment
├── data/
│   ├── dev/              # Dev database + media uploads (safe to delete)
│   │   └── media/
│   ├── test/             # Test database + media uploads
│   │   └── media/
│   └── prod/             # Prod database + media uploads (back this up!)
│       └── media/
├── docs/
│   └── MULTI_ENV_SETUP.md  # Auto-generated setup guide for the team
├── cloud_docs/frontend/
│   └── playwright.config.ts  # Playwright test config (if frontend exists)
└── .gitignore            # Updated to exclude .env.* and data/

How to Use

Step 1: Run the setup script

python3 scripts/setup_envs.py /path/to/your-project \
  --name "Your Project Name" \
  --dev-backend-port 8000 \
  --dev-frontend-port 3000 \
  --test-backend-port 8001 \
  --test-frontend-port 3001 \
  --prod-backend-port 8002 \
  --prod-frontend-port 4173 \
  --dev-user "Valina" \
  --test-user "Choco" \
  --app-module "server.main:app" \
  --frontend-dir "cloud_docs/frontend"

All flags except --name are optional and have sensible defaults.

Step 2: Start environments

# For Valina (Development)
./scripts/start-dev.sh        # Starts both backend (8000) and frontend (3000)

# For Choco (Testing)
./scripts/start-test.sh       # Starts both backend (8001) and frontend (3001)
./scripts/run-playwright-tests.sh  # Runs E2E tests

# For Production
./scripts/start-prod.sh       # Starts both backend (8002) and frontend (4173)

Step 2: Customize configs

Edit the generated .env.dev, .env.test, .env.prod files to add project-specific settings like API keys, external service URLs, etc.

Step 3: Start an environment

# For development (hot reload enabled)
./scripts/start-dev.sh

# For testing
./scripts/start-test.sh

# For production
./scripts/start-prod.sh

Each script loads its own .env.* file, uses its own port, and writes to its own data/ subdirectory.

Command Reference

python3 scripts/setup_envs.py <project_dir> --name <name> [options]
FlagDefaultDescription
project_dir(required)Path to the target project
--name(required)Project name, used in configs and docs
--dev-port8020Development server port
--test-port8010Testing server port
--prod-port8000Production server port
--dev-user(none)Developer name, shown in dev startup message
--test-user(none)Tester name, shown in test startup message
--db-typesqlitesqlite or postgres
--app-moduleserver.main:appUvicorn application module path
--dev-db(auto)Override dev database URL
--test-db(auto)Override test database URL
--prod-db(auto)Override prod database URL

Environment Differences at a Glance

SettingDev (Valina)Test (Choco)Prod
Backend Port800080018002
Frontend Port300030014173
DEBUGTrueTrueFalse
Hot ReloadYesNoNo
CORSAllow AllAllow AllRestricted
Rate LimitingOffOnOn
Workers1 (reload)1Auto (CPU cores)
Log LevelDEBUGINFOWARNING
Databasedata/dev/data/test/data/prod/
Mediadata/dev/media/data/test/media/data/prod/media/
Playwright Tests❌ Not recommended✅ Recommended❌ Never

Recommended Git Branch Strategy

For teams using this setup:

main ──────────── Production (start-prod.sh) - Ports 8002/4173
  ├── release/* ── Testing (start-test.sh + run-playwright-tests.sh) - Ports 8001/3001
  └── feature/* ── Development (start-dev.sh) - Ports 8000/3000
  1. Valina (Developer) works on feature/*, deploys to dev environment (8000/3000)
  2. Merge to release/*, Choco (Tester) validates on test environment (8001/3001)
  3. Choco runs Playwright tests: ./scripts/run-playwright-tests.sh
  4. Tester approves, merge to main, deploy to production (8002/4173)

Parallel Development and Testing

Key benefit: Valina and Choco can work simultaneously without conflicts!

Time  | Valina (Dev)              | Choco (Test)
------|---------------------------|---------------------------
14:00 | start-dev.sh (8000/3000)  | -
14:05 | Continue coding...        | start-test.sh (8001/3001)
14:10 | Continue coding...        | run-playwright-tests.sh
14:20 | Continue coding...        | Tests pass! Report results
14:25 | Continue coding...        | stop-test.sh

No port conflicts! No data interference! ✅

Important Notes

  • Existing files are not overwritten. If .env.dev already exists, the script skips it and prints a warning. Safe to re-run.
  • Backend startup scripts are uvicorn-specific. The generated start-backend-*.sh scripts use uvicorn commands. For other frameworks, modify the scripts after generation.
  • Frontend scripts support Vue/React. The generated start-frontend-*.sh scripts use npm run dev and npm run preview. For Vite projects, they work out of the box.
  • Production JWT secret must be changed. The generated .env.prod has a placeholder JWT_SECRET. Replace it with a strong random value before going live.
  • Back up production data. The data/prod/ directory contains the production database. Set up regular backups.
  • Playwright tests require Node.js. The test script requires Playwright to be installed: npm install -D @playwright/test
  • Test data cleanup. After running Playwright tests, consider cleaning up test data to keep the test environment clean.

Detailed Config Reference

For all environment variables and troubleshooting: read references/config-options.md

平台分布

OpenClaw

94.3%
按下载量换算1,456

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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