Ci Cd Generator logo

Ci Cd Generator

Organization
AIDotNet
ci-cd-generator

为GitHub Actions、GitLab CI、Azure DevOps和Jenkins生成CI/CD流水线,包含构建、测试、部署阶段、缓存和密钥管理。

Overview

PublisherAIDotNet
RepositoryMoYuCode
Skill nameci-cd-generator
Stars
85
Forks
17
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AIDotNet on GitHub. Read the source before you install it.

Installation

Install the Ci Cd Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AIDotNet/MoYuCode.git /tmp/MoYuCode
mkdir -p .claude/skills
cp -r /tmp/MoYuCode/skills/community/ci-cd-generator .claude/skills/ci-cd-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ci Cd Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ci Cd Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ci Cd Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CI/CD Generator Skill

Description

Generate continuous integration and deployment pipelines for various platforms.

Trigger

  • /cicd command
  • User requests CI/CD configuration
  • User needs deployment pipeline

Prompt

You are a DevOps expert that creates production-ready CI/CD pipelines.

GitHub Actions - Full Stack App

yaml
name: CI/CD Pipeline

on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]

env:
  NODE_VERSION: '20'
  DOTNET_VERSION: '8.0.x'

jobs:
  test-frontend:
    runs-on: ubuntu-latest
    defaults:
      run:
        working-directory: ./web
    steps:
      - uses: actions/checkout@v4
      
      - name: Setup Node.js
        uses: actions/setup-node@v4
        with:
          node-version: ${{ env.NODE_VERSION }}
          cache: 'npm'
          cache-dependency-path: web/package-lock.json
      
      - name: Install dependencies
        run: npm ci
      
      - name: Lint
        run: npm run lint
      
      - name: Type check
        run: npm run typecheck
      
      - name: Test
        run: npm run test -- --coverage
      
      - name: Build
        run: npm run build

  test-backend:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      
      - name: Setup .NET
        uses: actions/setup-dotnet@v4
        with:
          dotnet-version: ${{ env.DOTNET_VERSION }}
      
      - name: Restore dependencies
        run: dotnet restore
      
      - name: Build
        run: dotnet build --no-restore
      
      - name: Test
        run: dotnet test --no-build --verbosity normal

  deploy:
    needs: [test-frontend, test-backend]
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    environment: production
    steps:
      - uses: actions/checkout@v4
      
      - name: Deploy to Azure
        uses: azure/webapps-deploy@v2
        with:
          app-name: ${{ secrets.AZURE_APP_NAME }}
          publish-profile: ${{ secrets.AZURE_PUBLISH_PROFILE }}

GitLab CI

yaml
stages:
  - test
  - build
  - deploy

variables:
  NODE_VERSION: "20"

cache:
  key: ${CI_COMMIT_REF_SLUG}
  paths:
    - node_modules/
    - .npm/

test:
  stage: test
  image: node:${NODE_VERSION}
  script:
    - npm ci --cache .npm
    - npm run lint
    - npm run test -- --coverage
  coverage: '/Lines\s*:\s*(\d+\.?\d*)%/'
  artifacts:
    reports:
      coverage_report:
        coverage_format: cobertura
        path: coverage/cobertura-coverage.xml

build:
  stage: build
  image: docker:latest
  services:
    - docker:dind
  script:
    - docker build -t $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA .
    - docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA

deploy:
  stage: deploy
  only:
    - main
  script:
    - kubectl set image deployment/app app=$CI_REGISTRY_IMAGE:$CI_COMMIT_SHA

Docker Build & Push

yaml
- name: Build and push Docker image
  uses: docker/build-push-action@v5
  with:
    context: .
    push: true
    tags: |
      ghcr.io/${{ github.repository }}:latest
      ghcr.io/${{ github.repository }}:${{ github.sha }}
    cache-from: type=gha
    cache-to: type=gha,mode=max

Tags

ci-cd, devops, automation, github-actions, deployment

Compatibility

  • Codex: ✅
  • Claude Code: ✅

Frequently asked questions

What does the Ci Cd Generator AI skill do?

为GitHub Actions、GitLab CI、Azure DevOps和Jenkins生成CI/CD流水线,包含构建、测试、部署阶段、缓存和密钥管理。

Why use Ci Cd Generator on TypingMind?

Because you install it once and use it with any model. Ci Cd Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ci Cd Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AIDotNet/MoYuCode/tree/main/skills/community/ci-cd-generator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ci Cd Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ci Cd Generator?

As many as you like. As long as a model supports skills, you can use Ci Cd Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ci Cd Generator AI skill free?

Yes. It is published on GitHub by AIDotNet under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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