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Agent Skill · 开发

ci-cd-pipeline-builder(CI CD 管道构建器)

ci-cd-pipeline-builder 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。

ci-cd-pipeline-builder 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 11,818。

总安装 1,572周安装 63GitHub Stars 103下载 509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:ci-cd-pipeline-builder(CI CD 管道构建器)
来源仓库:https://github.com/borghei/claude-skills
仓库路径:skills/ci-cd-pipeline-builder
安装命令:
npx skills add https://github.com/borghei/claude-skills --skill ci-cd-pipeline-builder
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/borghei/claude-skills --skill ci-cd-pipeline-builder

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

根据项目技术栈自动生成 CI/CD 流水线配置,支持主流云平台。内置缓存优化、矩阵构建与安全扫描插件推荐。提供蓝绿部署与金丝雀发布策略模板,降低上线风险。部署密钥与敏感变量必须通过 Vault 或 Secrets Manager 管理。

ci-cd-pipeline-builder 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ci-cd-pipeline-builder

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/borghei/claude-skills --skill ci-cd-pipeline-b…;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

    它需要需要联网,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

ci-cd-pipeline-builder 怎么安装?

在终端执行 npx skills add https://github.com/borghei/claude-skills --skill ci-cd-pipeline-builder。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ci-cd-pipeline-builder 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。

ci-cd-pipeline-builder 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

ci-cd-pipeline-builder 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。

ci-cd-pipeline-builder 用的人多吗?

公开数据是累计安装 1,572 次,近一周安装 63 次,下载 509 次,GitHub 103 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。

ci-cd-pipeline-builder 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
ci-cd-pipeline-builder

CI CD 管道构建器 · 本页

1,572103需要联网未明确通过

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

CI/CD Pipeline Builder

Tier: POWERFUL Category: Engineering / DevOps Maintainer: Claude Skills Team

Overview

Generate production-grade CI/CD pipelines from detected project stack signals. Analyzes lockfiles, manifests, and scripts to produce optimized pipelines with proper caching, matrix strategies, security scanning, and deployment gates. Supports GitHub Actions, GitLab CI, CircleCI, and Buildkite with deployment strategies including blue-green, canary, and rolling updates.

Keywords

CI/CD, GitHub Actions, GitLab CI, pipeline, deployment, caching, matrix builds, blue-green deployment, canary deployment, security scanning, SAST, container builds, environment gates

Core Capabilities

1. Stack Detection

  • Language/runtime detection from lockfiles and manifests
  • Package manager inference from lock file format
  • Build/test/lint command extraction from scripts
  • Framework detection (Next.js, FastAPI, Go modules, etc.)
  • Infrastructure detection (Docker, Kubernetes, Terraform)

2. Pipeline Generation

  • Lint, test, build, deploy stages with correct dependencies
  • Caching strategies matched to package manager
  • Matrix builds for multi-version support
  • Artifact passing between jobs
  • Conditional execution (path filters, branch rules)

3. Deployment Strategies

  • Blue-green with instant rollback
  • Canary with percentage-based traffic shifting
  • Rolling updates with health checks
  • Feature flags integration
  • Manual approval gates for production

4. Security Integration

  • SAST scanning (CodeQL, Semgrep, Snyk)
  • Dependency vulnerability scanning
  • Container image scanning (Trivy, Grype)
  • Secret scanning in CI
  • SBOM generation

When to Use

  • Bootstrapping CI/CD for a new repository
  • Migrating between CI platforms
  • Optimizing slow or flaky pipelines
  • Adding deployment stages to an existing CI-only pipeline
  • Implementing security scanning in the pipeline
  • Setting up multi-environment deployment (staging, production)

Stack Detection Heuristics

File Found                    → Inference
─────────────────────────────────────────────────
package-lock.json             → Node.js + npm
pnpm-lock.yaml                → Node.js + pnpm
yarn.lock                     → Node.js + yarn
bun.lockb                     → Bun
requirements.txt / Pipfile    → Python + pip/pipenv
pyproject.toml + uv.lock      → Python + uv
poetry.lock                   → Python + poetry
go.mod                        → Go
Cargo.lock                    → Rust
Gemfile.lock                  → Ruby
composer.lock                 → PHP
next.config.*                 → Next.js (Node.js)
nuxt.config.*                 → Nuxt (Node.js)
Dockerfile                    → Container build needed
docker-compose.yml            → Multi-service setup
terraform/*.tf                → Infrastructure as Code
k8s/ or kubernetes/           → Kubernetes deployment

GitHub Actions Pipeline Templates

Node.js (pnpm + Vitest + Next.js)

name: CI/CD

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

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

env:
  NODE_VERSION: '20'
  PNPM_VERSION: '9'

jobs:
  lint-and-typecheck:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: pnpm/action-setup@v4
        with:
          version: ${{ env.PNPM_VERSION }}
      - uses: actions/setup-node@v4
        with:
          node-version: ${{ env.NODE_VERSION }}
          cache: 'pnpm'
      - run: pnpm install --frozen-lockfile
      - run: pnpm lint
      - run: pnpm typecheck

  test:
    runs-on: ubuntu-latest
    needs: lint-and-typecheck
    services:
      postgres:
        image: postgres:16
        env:
          POSTGRES_USER: test
          POSTGRES_PASSWORD: test
          POSTGRES_DB: testdb
        ports: ['5432:5432']
        options: >-
          --health-cmd pg_isready
          --health-interval 10s
          --health-timeout 5s
          --health-retries 5
    steps:
      - uses: actions/checkout@v4
      - uses: pnpm/action-setup@v4
        with:
          version: ${{ env.PNPM_VERSION }}
      - uses: actions/setup-node@v4
        with:
          node-version: ${{ env.NODE_VERSION }}
          cache: 'pnpm'
      - run: pnpm install --frozen-lockfile
      - run: pnpm test:ci
        env:
          DATABASE_URL: postgresql://test:test@localhost:5432/testdb

  build:
    runs-on: ubuntu-latest
    needs: test
    steps:
      - uses: actions/checkout@v4
      - uses: pnpm/action-setup@v4
        with:
          version: ${{ env.PNPM_VERSION }}
      - uses: actions/setup-node@v4
        with:
          node-version: ${{ env.NODE_VERSION }}
          cache: 'pnpm'
      - run: pnpm install --frozen-lockfile
      - run: pnpm build
      - uses: actions/upload-artifact@v4
        with:
          name: build-output
          path: .next/
          retention-days: 1

  security-scan:
    runs-on: ubuntu-latest
    permissions:
      security-events: write
    steps:
      - uses: actions/checkout@v4
      - uses: github/codeql-action/init@v3
        with:
          languages: javascript-typescript
      - uses: github/codeql-action/analyze@v3

  deploy-staging:
    if: github.ref == 'refs/heads/main' && github.event_name == 'push'
    needs: [build, security-scan]
    runs-on: ubuntu-latest
    environment:
      name: staging
      url: https://staging.myapp.com
    steps:
      - uses: actions/checkout@v4
      - uses: actions/download-artifact@v4
        with:
          name: build-output
          path: .next/
      - name: Deploy to staging
        run: |
          # Replace with your deployment command
          echo "Deploying to staging..."
        env:
          DEPLOY_TOKEN: ${{ secrets.STAGING_DEPLOY_TOKEN }}

  deploy-production:
    if: github.ref == 'refs/heads/main' && github.event_name == 'push'
    needs: deploy-staging
    runs-on: ubuntu-latest
    environment:
      name: production
      url: https://myapp.com
    steps:
      - uses: actions/checkout@v4
      - uses: actions/download-artifact@v4
        with:
          name: build-output
          path: .next/
      - name: Deploy to production
        run: |
          echo "Deploying to production..."
        env:
          DEPLOY_TOKEN: ${{ secrets.PROD_DEPLOY_TOKEN }}

Python (uv + pytest + FastAPI)

name: CI/CD

on:
  push:
    branches: [main]
  pull_request:

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v4
      - run: uv sync --frozen
      - run: uv run ruff check .
      - run: uv run ruff format --check .
      - run: uv run mypy src/

  test:
    runs-on: ubuntu-latest
    needs: lint
    strategy:
      matrix:
        python-version: ['3.11', '3.12', '3.13']
    services:
      postgres:
        image: postgres:16
        env:
          POSTGRES_USER: test
          POSTGRES_PASSWORD: test
          POSTGRES_DB: testdb
        ports: ['5432:5432']
        options: --health-cmd pg_isready --health-interval 10s --health-timeout 5s --health-retries 5
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v4
        with:
          python-version: ${{ matrix.python-version }}
      - run: uv sync --frozen
      - run: uv run pytest --cov --cov-report=xml -v
        env:
          DATABASE_URL: postgresql://test:test@localhost:5432/testdb
      - uses: codecov/codecov-action@v4
        if: matrix.python-version == '3.12'
        with:
          file: coverage.xml

  build-container:
    needs: test
    runs-on: ubuntu-latest
    permissions:
      contents: read
      packages: write
    steps:
      - uses: actions/checkout@v4
      - uses: docker/setup-buildx-action@v3
      - uses: docker/login-action@v3
        with:
          registry: ghcr.io
          username: ${{ github.actor }}
          password: ${{ secrets.GITHUB_TOKEN }}
      - uses: docker/build-push-action@v6
        with:
          context: .
          push: ${{ github.ref == 'refs/heads/main' }}
          tags: ghcr.io/${{ github.repository }}:${{ github.sha }}
          cache-from: type=gha
          cache-to: type=gha,mode=max

  container-scan:
    needs: build-container
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - uses: aquasecurity/trivy-action@master
        with:
          image-ref: ghcr.io/${{ github.repository }}:${{ github.sha }}
          severity: 'CRITICAL,HIGH'
          exit-code: '1'

Deployment Strategy Decision Framework

How critical is zero-downtime?
│
├─ Critical (payment processing, real-time systems)
│  └─ BLUE-GREEN DEPLOYMENT
│     Pro: Instant rollback, zero-downtime guaranteed
│     Con: Requires 2x infrastructure during deployment
│
├─ Important but can tolerate brief errors
│  ├─ Need to validate with real traffic first?
│  │  └─ CANARY DEPLOYMENT
│  │     Pro: Test with small % of traffic before full rollout
│  │     Con: Complex routing, need observability for canary metrics
│  │
│  └─ Standard web app with health checks
│     └─ ROLLING UPDATE
│        Pro: Simple, built into K8s/ECS, gradual rollout
│        Con: Both versions serve traffic during rollout
│
└─ Development/staging environment
   └─ RECREATE (stop old, start new)
      Pro: Simplest, cleanest
      Con: Brief downtime during deployment

Caching Strategy Reference

Package ManagerCache PathKey Pattern
npm~/.npm${{runner.os}}-npm-${{hashFiles('package-lock.json')}}
pnpmDetected by setup-nodecache: 'pnpm' in setup-node
yarn~/.cache/yarn${{runner.os}}-yarn-${{hashFiles('yarn.lock')}}
pip~/.cache/pip${{runner.os}}-pip-${{hashFiles('requirements.txt')}}
uv~/.cache/uvHandled by setup-uv
Go~/go/pkg/mod${{runner.os}}-go-${{hashFiles('go.sum')}}
Cargo~/.cargo/registry${{runner.os}}-cargo-${{hashFiles('Cargo.lock')}}
DockerGHA cachecache-from: type=gha in build-push-action

Pipeline Optimization Techniques

1. Path Filtering (Skip Unnecessary Runs)

on:
  push:
    paths:
      - 'src/**'
      - 'tests/**'
      - 'package.json'
      - 'pnpm-lock.yaml'
    paths-ignore:
      - '**.md'
      - 'docs/**'
      - '.github/ISSUE_TEMPLATE/**'

2. Job Dependency Graph

lint ──────┐
           ├──→ test ──→ build ──→ deploy-staging ──→ deploy-production
typecheck ─┘                │
                            └──→ security-scan

3. Matrix Strategy with Fail-Fast

strategy:
  fail-fast: true  # cancel all if one fails
  matrix:
    node-version: [18, 20, 22]
    os: [ubuntu-latest]
    include:
      - node-version: 20
        os: macos-latest  # test one combo on macOS

GitLab CI Equivalent

stages:
  - validate
  - test
  - build
  - deploy

variables:
  NODE_VERSION: "20"

.node-setup: &node-setup
  image: node:${NODE_VERSION}
  cache:
    key: ${CI_COMMIT_REF_SLUG}
    paths:
      - node_modules/
      - .pnpm-store/
  before_script:
    - corepack enable
    - pnpm install --frozen-lockfile

lint:
  stage: validate
  <<: *node-setup
  script:
    - pnpm lint
    - pnpm typecheck

test:
  stage: test
  <<: *node-setup
  services:
    - postgres:16
  variables:
    POSTGRES_DB: testdb
    POSTGRES_USER: test
    POSTGRES_PASSWORD: test
    DATABASE_URL: postgresql://test:test@postgres:5432/testdb
  script:
    - pnpm test:ci
  coverage: '/All files[^|]*\|[^|]*\s+([\d\.]+)/'

build:
  stage: build
  <<: *node-setup
  script:
    - pnpm build
  artifacts:
    paths:
      - .next/
    expire_in: 1 hour

deploy_staging:
  stage: deploy
  environment:
    name: staging
    url: https://staging.myapp.com
  rules:
    - if: $CI_COMMIT_BRANCH == "main"
  script:
    - echo "Deploy to staging"

deploy_production:
  stage: deploy
  environment:
    name: production
    url: https://myapp.com
  rules:
    - if: $CI_COMMIT_BRANCH == "main"
      when: manual
  needs: [deploy_staging]
  script:
    - echo "Deploy to production"

Validation Checklist

Before merging a generated pipeline:

  1. YAML parses without syntax errors
  2. All referenced commands exist in the repository (test, lint, build)
  3. Cache strategy matches the detected package manager
  4. Required secrets are documented (not embedded in YAML)
  5. Branch protection rules match organization policy
  6. Deployment jobs are gated by protected environments
  7. Security scanning runs on the appropriate code paths
  8. Artifact retention is set (do not keep build artifacts indefinitely)
  9. Concurrency group prevents duplicate runs on the same branch
  10. Path filters exclude documentation-only changes from full CI runs

Common Pitfalls

  • Copying pipelines between projects without adapting to the actual stack
  • No concurrency control leading to redundant parallel runs on rapid pushes
  • Missing cache keys causing cache misses on every run (slow builds)
  • Running full matrix on every PR when only main needs multi-version testing
  • Hardcoding secrets in YAML instead of using CI secret stores
  • No path filtering so documentation changes trigger full build+test+deploy
  • Deploy jobs without environment gates allowing accidental production deployments
  • No artifact retention policy causing storage costs to grow indefinitely

Best Practices

  1. Detect stack first, then generate pipeline — never guess at build commands
  2. Keep the generated baseline under version control and customize incrementally
  3. One optimization at a time — add caching, then matrix, then split jobs
  4. Require green CI before any deployment job can execute
  5. Use protected environments for production credentials and manual approval gates
  6. Track pipeline duration and flakiness as first-class engineering metrics
  7. Separate deploy jobs from CI jobs to keep feedback fast for developers
  8. Regenerate the pipeline when the stack changes significantly (new language, new framework)

Troubleshooting

ProblemCauseSolution
Pipeline YAML fails validationIndentation errors or invalid key namesRun yamllint locally before committing; use the CI platform's built-in linter (e.g., act for GitHub Actions, gitlab-ci-lint for GitLab)
Cache misses on every runCache key does not include the correct lockfile hashVerify the hashFiles() path matches the actual lockfile location; check the Caching Strategy Reference table above
Matrix build times explodeRunning full OS + version matrix on every PRRestrict the full matrix to main branch pushes; run a single representative version on PRs
Deployment job triggers on PRsMissing branch/event guard on deploy jobsAdd if: github.ref == 'refs/heads/main' && github.event_name == 'push' or equivalent platform condition
Service containers fail to startHealth check misconfigured or image not foundPin the service image to a specific major version; confirm health check command exists in the image
Secret not available in workflowSecret not added to the repository or environment settingsAdd the secret via the CI platform's secrets UI; ensure the job references the correct environment name
Build artifact missing in deploy jobArtifact name mismatch or retention expiredEnsure upload-artifact and download-artifact use the same name value; set retention-days high enough to survive the full pipeline

Success Criteria

  • Pipeline generates valid YAML that passes platform-native linting on first attempt for detected stacks
  • Build times stay under 10 minutes for lint + test + build stages combined (excluding deploy)
  • Cache hit rate exceeds 90% on repeat runs with unchanged lockfiles
  • Security scanning (SAST + dependency + container) executes on every push to main without manual triggers
  • Deployment to staging is fully automated; production requires exactly one manual approval gate
  • Pipeline flakiness rate remains below 2% over a rolling 30-day window
  • Zero hardcoded secrets in generated pipeline YAML; all sensitive values reference platform secret stores

Scope & Limitations

This skill covers:

  • Generating CI/CD pipelines for GitHub Actions, GitLab CI, CircleCI, and Buildkite
  • Stack detection from lockfiles, manifests, Dockerfiles, and infrastructure-as-code definitions
  • Deployment strategy selection (blue-green, canary, rolling, recreate) with decision framework
  • Pipeline optimization including caching, matrix builds, path filtering, and concurrency control

This skill does NOT cover:

  • Runtime infrastructure provisioning or cloud resource management (see engineering/saas-scaffolder)
  • Application-level security hardening beyond CI-integrated scanning (see engineering/skill-security-auditor)
  • Monitoring, alerting, and observability configuration after deployment (see engineering/observability-designer)
  • Database migration orchestration during deployments (see engineering/migration-architect)

Integration Points

SkillIntegrationData Flow
engineering/dependency-auditorFeeds vulnerability scan results into pipeline security gatesAuditor findings trigger pipeline failure or warning annotations
engineering/release-managerCoordinates versioning and changelog with deploy stagesRelease tags drive conditional deployment job execution
engineering/observability-designerPost-deploy health checks and alerting complement pipeline gatesPipeline triggers smoke tests; observability confirms deployment health
engineering/env-secrets-managerManages secrets referenced by pipeline environment variablesSecret rotation policies feed into pipeline secret store configuration
engineering/migration-architectDatabase migrations run as a pre-deploy step in the pipelineMigration status gates the application deployment job
engineering/runbook-generatorGenerates rollback runbooks aligned with deployment strategyPipeline failure triggers link to the relevant rollback runbook

平台分布

Codex

34.85%
按下载量换算177

Claude

31.6%
按下载量换算161

Cursor

19.83%
按下载量换算101

Gemini CLI

9.63%
按下载量换算49

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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