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Agent Skill · 研究检索

moai-platform-deployment(moai 平台部署)

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

moai-platform-deployment 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 44,644。

总安装 903周安装 38GitHub Stars 964下载 316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
unknown

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:moai-platform-deployment(moai 平台部署)
来源仓库:https://github.com/modu-ai/moai-adk
仓库路径:skills/moai-platform-deployment
安装命令:
npx skills add https://github.com/modu-ai/moai-adk --skill moai-platform-deployment
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/modu-ai/moai-adk --skill moai-platform-deployment

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助云资源、部署、容器和基础设施运维自动化任务。适合检查配置、整理部署步骤或分析资源状态。moai-platform-deployment 属于研究检索类 Skill,可作为该场景下的辅助能力补充。通过 npx skills add 命令从 moai-adk 仓库安装并使用。

涉及删除资源或修改网络配置时应先确认影响范围。具体用法可结合来源仓库 README 进一步核验实际功能边界。

来源仓库内路径:skills/moai-platform-deployment

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/modu-ai/moai-adk --skill moai-platform-deploym…;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

moai-platform-deployment 怎么安装?

在终端执行 npx skills add https://github.com/modu-ai/moai-adk --skill moai-platform-deployment。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

moai-platform-deployment 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

moai-platform-deployment 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。

moai-platform-deployment 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

moai-platform-deployment 用的人多吗?

公开数据是累计安装 903 次,近一周安装 38 次,下载 316 次,GitHub 964 星。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。

moai-platform-deployment 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、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。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
moai-platform-deployment

moai 平台部署 · 本页

903964接触敏感数据未明确有提醒

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

Deployment Platform Specialist

Comprehensive deployment platform guide covering Vercel (edge-first), Railway (container-first), and Convex (real-time backend).


Quick Platform Selection

When to Use Each Platform

Vercel - Edge-First Deployment:

  • Next.js applications with SSR/SSG
  • Global CDN distribution required
  • Sub-50ms edge latency critical
  • Preview deployments for team collaboration
  • Managed storage needs (KV, Blob, Postgres)

Railway - Container-First Deployment:

  • Full-stack containerized applications
  • Custom runtime environments
  • Multi-service architectures
  • Persistent volume storage
  • WebSocket/gRPC long-lived connections

Convex - Real-Time Backend:

  • Collaborative real-time applications
  • Reactive data synchronization
  • TypeScript-first backend needs
  • Optimistic UI updates
  • Document-oriented data models

Decision Guide

By Application Type

Web Applications (Frontend + API):

  • Next.js → Vercel (optimal integration)
  • React/Vue with custom API → Railway (flexible)
  • Real-time collaborative → Convex + Vercel

Mobile Backends:

  • REST/GraphQL → Railway (stable connections)
  • Real-time sync → Convex (reactive queries)
  • Edge API → Vercel (global latency)

Full-Stack Monoliths:

  • Containerized → Railway (Docker support)
  • Serverless → Vercel (Next.js API routes)
  • Real-time → Convex (built-in reactivity)

By Infrastructure Needs

Compute Requirements:

  • Edge compute → Vercel (30+ edge locations)
  • Custom runtimes → Railway (Docker flexibility)
  • Serverless TypeScript → Convex (managed runtime)

Storage Requirements:

  • Redis/KV → Vercel KV or Railway
  • PostgreSQL → Vercel Postgres or Railway
  • File storage → Vercel Blob or Railway volumes
  • Document DB → Convex (built-in)

Networking Requirements:

  • CDN distribution → Vercel (built-in)
  • Private networking → Railway (service mesh)
  • Real-time WebSocket → Convex (built-in) or Railway

Common Deployment Patterns

Pattern 1: Next.js with Database

Stack: Vercel + Vercel Postgres/KV

Setup:

  1. Deploy Next.js app to Vercel
  2. Provision Vercel Postgres for database
  3. Use Vercel KV for session/cache
  4. Configure environment variables
  5. Enable ISR for dynamic content

Best For: Web apps with standard database needs, e-commerce, content sites

Pattern 2: Containerized Multi-Service

Stack: Railway + Docker

Setup:

  1. Create multi-stage Dockerfile
  2. Configure railway.toml for services
  3. Set up private networking
  4. Configure persistent volumes
  5. Enable auto-scaling

Best For: Microservices, complex backends, custom tech stacks

Pattern 3: Real-Time Collaborative App

Stack: Convex + Vercel/Railway (frontend)

Setup:

  1. Initialize Convex backend
  2. Define schema and server functions
  3. Deploy frontend to Vercel/Railway
  4. Configure Convex provider
  5. Implement optimistic updates

Best For: Collaborative tools, live dashboards, chat applications

Pattern 4: Hybrid Edge + Container

Stack: Vercel (frontend/edge) + Railway (backend services)

Setup:

  1. Deploy Next.js frontend to Vercel
  2. Deploy backend services to Railway
  3. Configure CORS and API endpoints
  4. Set up edge middleware for routing
  5. Use private networking for Railway

Best For: High-performance apps, global distribution with complex backends

Pattern 5: Serverless Full-Stack

Stack: Vercel (frontend + API routes) + Convex (backend)

Setup:

  1. Build Next.js app with API routes
  2. Initialize Convex for data layer
  3. Configure authentication (Clerk/Auth0)
  4. Deploy frontend to Vercel
  5. Connect Convex client

Best For: Rapid prototyping, startups, real-time web apps


Essential Configuration

Vercel Quick Start

vercel.json:

{
  "$schema": "https://openapi.vercel.sh/vercel.json",
  "framework": "nextjs",
  "regions": ["iad1", "sfo1", "fra1"],
  "functions": {
    "app/api/**/*.ts": {
      "memory": 1024,
      "maxDuration": 10
    }
  }
}

Edge Function:

export const runtime = "edge"
export const preferredRegion = ["iad1", "sfo1"]

export async function GET(request: Request) {
  const country = request.geo?.country || "Unknown"
  return Response.json({ country })
}

Railway Quick Start

railway.toml:

[build]
builder = "DOCKERFILE"
dockerfilePath = "Dockerfile"

[deploy]
healthcheckPath = "/health"
healthcheckTimeout = 100
restartPolicyType = "ON_FAILURE"
numReplicas = 2

[deploy.resources]
memory = "2GB"
cpu = "2.0"

Multi-Stage Dockerfile:

# Builder stage
FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Runner stage
FROM node:20-alpine
WORKDIR /app
ENV NODE_ENV=production
RUN addgroup -g 1001 -S nodejs && adduser -S appuser -u 1001
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/dist ./dist
USER appuser
EXPOSE 3000
CMD ["node", "dist/main.js"]

Convex Quick Start

convex/schema.ts:

import { defineSchema, defineTable } from "convex/server"
import { v } from "convex/values"

export default defineSchema({
  messages: defineTable({
    text: v.string(),
    userId: v.id("users"),
    timestamp: v.number(),
  })
    .index("by_timestamp", ["timestamp"])
    .searchIndex("search_text", {
      searchField: "text",
      filterFields: ["userId"],
    }),
})

React Integration:

import { useQuery, useMutation } from "convex/react"
import { api } from "../convex/_generated/api"

export function Messages() {
  const messages = useQuery(api.messages.list)
  const sendMessage = useMutation(api.messages.send)

  if (!messages) return <div>Loading...</div>

  return (
    <div>
      {messages.map((msg) => (
        <div key={msg._id}>{msg.text}</div>
      ))}
    </div>
  )
}

CI/CD Integration

GitHub Actions - Vercel

name: Deploy to Vercel
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: amondnet/vercel-action@v25
        with:
          vercel-token: ${{ secrets.VERCEL_TOKEN }}
          vercel-org-id: ${{ secrets.ORG_ID }}
          vercel-project-id: ${{ secrets.PROJECT_ID }}

GitHub Actions - Railway

name: Deploy to Railway
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: npm install -g @railway/cli
      - run: railway up --detach
        env:
          RAILWAY_TOKEN: ${{ secrets.RAILWAY_TOKEN }}

GitHub Actions - Convex

name: Deploy to Convex
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
      - run: npm ci
      - run: npx convex deploy
        env:
          CONVEX_DEPLOY_KEY: ${{ secrets.CONVEX_DEPLOY_KEY }}

Advanced Patterns

Blue-Green Deployment (Vercel)

Deploy new version, test on preview URL, then switch production alias using Vercel SDK for zero-downtime releases.

Multi-Region (Railway)

Configure deployment regions in railway.toml:

[deploy.regions]
name = "us-west"
replicas = 2

[[deploy.regions]]
name = "eu-central"
replicas = 1

Optimistic Updates (Convex)

const sendMessage = useMutation(api.messages.send)

const handleSend = (text: string) => {
  sendMessage({ text })
    .then(() => console.log("Sent"))
    .catch(() => console.log("Failed, rolled back"))
}

Platform-Specific Details

For detailed platform-specific patterns, configuration options, and advanced use cases, see:

  • reference/vercel.md - Edge Functions, ISR, Analytics, Storage
  • reference/railway.md - Docker, Multi-Service, Volumes, Scaling
  • reference/convex.md - Reactive Queries, Server Functions, File Storage
  • reference/comparison.md - Feature Matrix, Pricing, Migration Guides

Works Well With

  • moai-domain-backend for backend architecture patterns
  • moai-domain-frontend for frontend integration
  • moai-lang-typescript for TypeScript best practices
  • moai-lang-python for Python deployment (Railway)
  • moai-platform-auth for authentication integration
  • moai-platform-database for database patterns

Status: Production Ready Version: 2.0.0 Updated: 2026-02-09 Platforms: Vercel, Railway, Convex

Common Rationalizations

RationalizationReality
"I will configure the deployment platform after development is complete"Deployment configuration affects build output, environment variables, and runtime behavior. Configure early.
"Preview deployments are optional"Preview deployments catch deployment-specific bugs before production. They cost little and save a lot.
"Environment variables are the same across all environments"Production, staging, and development need different database URLs, API keys, and feature flags. One set of env vars is a security risk.
"Serverless cold starts are negligible"Cold starts add 200-2000ms latency on first request. For user-facing APIs, this matters. Measure and mitigate.
"I do not need a rollback strategy, I can just redeploy"Redeployment takes minutes. Rollback takes seconds. When production is down, seconds matter.

Red Flags

  • Production environment variables visible in build logs
  • No preview deployment configured for pull requests
  • Single environment used for both staging and production
  • No rollback mechanism documented or tested
  • Build artifacts include development dependencies or source maps

Verification

  • Environment variables separated by environment (dev, staging, production)
  • Preview deployments configured for pull requests (show platform config)
  • Rollback procedure documented and tested (show rollback command or process)
  • Production build excludes development dependencies and source maps
  • Deployment succeeds from a clean git checkout (no local state dependency)
  • Cold start time measured for serverless functions (show timing data)

Refactor Notes

R4 audit verdict (2026-04-23): REFACTOR — shrink triplet to Vercel-only primary; Railway/Convex as documentation-only SPEC: SPEC-V3R2-WF-001 §6.2 line 271 Refactor scope (deferred to future sub-SPEC):

  • Elevate Vercel as primary platform with full guidance; demote Railway and Convex to doc-only references
  • Move Railway and Convex deep-dives into Level-3 modules
  • Add CI/CD pipeline patterns section (GitHub Actions, Vercel CI integration)

This skill is retained in v3.0 but its body will be restructured in a follow-up SPEC.

平台分布

Codex

36.48%
按下载量换算115

Claude

31.26%
按下载量换算99

Cursor

16.88%
按下载量换算53

Gemini CLI

8.86%
按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

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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