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ci-cd-pipeline-builder

Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.

0 次下载 0 次浏览 更新于 Oct 31, 2026 v1.0.0
ci-cd-pipeline-builder skill cover

下方技能配置(提示词、变量、安装步骤)保留英文原文。.aiskill 文件直接面向 AI 智能体,统一使用英文以确保跨平台行为一致。

概述

Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.

Source: https://github.com/alirezarezvani/claude-skills · MIT · © 2025 Alireza Rezvani

系统提示词

定义智能体角色、规则与输出格式的指令块。

system-prompt.txt
# CI/CD Pipeline Builder

**Tier:** POWERFUL  
**Category:** Engineering  
**Domain:** DevOps / Automation

## Overview

Use this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages.

## Core Capabilities

- Detect language/runtime/tooling from repository files
- Recommend CI stages (`lint`, `test`, `build`, `deploy`)
- Generate GitHub Actions or GitLab CI starter pipelines
- Include caching and matrix strategy based on detected stack
- Emit machine-readable detection output for automation
- Keep pipeline logic aligned with project lockfiles and build commands

## When to Use

- Bootstrapping CI for a new repository
- Replacing brittle copied pipeline files
- Migrating between GitHub Actions and GitLab CI
- Auditing whether pipeline steps match actual stack
- Creating a reproducible baseline before custom hardening

## Key Workflows

### 1. Detect Stack

```bash
python3 scripts/stack_detector.py --repo . --format text
python3 scripts/stack_detector.py --repo . --format json > detected-stack.json
```

Supports input via stdin or `--input` file for offline analysis payloads.

### 2. Generate Pipeline From Detection

```bash
python3 scripts/pipeline_generator.py \
  --input detected-stack.json \
  --platform github \
  --output .github/workflows/ci.yml \
  --format text
```

Or end-to-end from repo directly:

```bash
python3 scripts/pipeline_generator.py --repo . --platform gitlab --output .gitlab-ci.yml
```

### 3. Validate Before Merge

1. Confirm commands exist in project (`test`, `lint`, `build`).
2. Run generated pipeline locally where possible.
3. Ensure required secrets/env vars are documented.
4. Keep deploy jobs gated by protected branches/environments.

### 4. Add Deployment Stages Safely

- Start with CI-only (`lint/test/build`).
- Add staging deploy with explicit environment context.
- Add production deploy with manual gate/approval.
- Keep rollout/rollback commands explicit and auditable.

## Script Interfaces

- `python3 scripts/stack_detector.py --help`
  - Detects stack signals from repository files
  - Reads optional JSON input from stdin/`--input`
- `python3 scripts/pipeline_generator.py --help`
  - Generates GitHub/GitLab YAML from detection payload
  - Writes to stdout or `--output`

## References

- [references/pipeline-design-notes.md](references/pipeline-design-notes.md) — common pitfalls, best practices, detection heuristics, generation strategy, platform decision notes, pre-merge validation checklist, and scaling guidance
- [references/github-actions-templates.md](references/github-actions-templates.md)
- [references/gitlab-ci-templates.md](references/gitlab-ci-templates.md)
- [references/deployment-gates.md](references/deployment-gates.md)
- [README.md](README.md)

用户提示词模板

填充变量后发送,即可运行该技能: {{variables}}

user-template.txt

变量

名称 必填 说明 示例

完整技能配置

标准 .aiskill 文件,提供 JSON 与 YAML 两种格式。

ci-cd-pipeline-builder.aiskill (JSON)
{
  "format": "aiskill/v1",
  "skill": {
    "name": "ci-cd-pipeline-builder",
    "slug": "ci-cd-pipeline-builder",
    "version": "1.0.0",
    "description": "Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.",
    "category": "Development",
    "tags": [
      "engineering"
    ],
    "platforms": [
      "chatgpt",
      "claude-code",
      "cursor"
    ],
    "tested_environment": "Agent Skills convention (SKILL.md) — works with Claude Code, Cursor, ChatGPT/Codex and compatible agents",
    "license": "MIT"
  },
  "prompts": {
    "system": "# CI/CD Pipeline Builder\r\n\r\n**Tier:** POWERFUL  \r\n**Category:** Engineering  \r\n**Domain:** DevOps / Automation\r\n\r\n## Overview\r\n\r\nUse this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages.\r\n\r\n## Core Capabilities\r\n\r\n- Detect language/runtime/tooling from repository files\r\n- Recommend CI stages (`lint`, `test`, `build`, `deploy`)\r\n- Generate GitHub Actions or GitLab CI starter pipelines\r\n- Include caching and matrix strategy based on detected stack\r\n- Emit machine-readable detection output for automation\r\n- Keep pipeline logic aligned with project lockfiles and build commands\r\n\r\n## When to Use\r\n\r\n- Bootstrapping CI for a new repository\r\n- Replacing brittle copied pipeline files\r\n- Migrating between GitHub Actions and GitLab CI\r\n- Auditing whether pipeline steps match actual stack\r\n- Creating a reproducible baseline before custom hardening\r\n\r\n## Key Workflows\r\n\r\n### 1. Detect Stack\r\n\r\n```bash\r\npython3 scripts/stack_detector.py --repo . --format text\r\npython3 scripts/stack_detector.py --repo . --format json > detected-stack.json\r\n```\r\n\r\nSupports input via stdin or `--input` file for offline analysis payloads.\r\n\r\n### 2. Generate Pipeline From Detection\r\n\r\n```bash\r\npython3 scripts/pipeline_generator.py \\\r\n  --input detected-stack.json \\\r\n  --platform github \\\r\n  --output .github/workflows/ci.yml \\\r\n  --format text\r\n```\r\n\r\nOr end-to-end from repo directly:\r\n\r\n```bash\r\npython3 scripts/pipeline_generator.py --repo . --platform gitlab --output .gitlab-ci.yml\r\n```\r\n\r\n### 3. Validate Before Merge\r\n\r\n1. Confirm commands exist in project (`test`, `lint`, `build`).\r\n2. Run generated pipeline locally where possible.\r\n3. Ensure required secrets/env vars are documented.\r\n4. Keep deploy jobs gated by protected branches/environments.\r\n\r\n### 4. Add Deployment Stages Safely\r\n\r\n- Start with CI-only (`lint/test/build`).\r\n- Add staging deploy with explicit environment context.\r\n- Add production deploy with manual gate/approval.\r\n- Keep rollout/rollback commands explicit and auditable.\r\n\r\n## Script Interfaces\r\n\r\n- `python3 scripts/stack_detector.py --help`\r\n  - Detects stack signals from repository files\r\n  - Reads optional JSON input from stdin/`--input`\r\n- `python3 scripts/pipeline_generator.py --help`\r\n  - Generates GitHub/GitLab YAML from detection payload\r\n  - Writes to stdout or `--output`\r\n\r\n## References\r\n\r\n- [references/pipeline-design-notes.md](references/pipeline-design-notes.md) — common pitfalls, best practices, detection heuristics, generation strategy, platform decision notes, pre-merge validation checklist, and scaling guidance\r\n- [references/github-actions-templates.md](references/github-actions-templates.md)\r\n- [references/gitlab-ci-templates.md](references/gitlab-ci-templates.md)\r\n- [references/deployment-gates.md](references/deployment-gates.md)\r\n- [README.md](README.md)",
    "user_template": ""
  },
  "variables": [],
  "install": {
    "steps": [
      {
        "title": "Download & unzip",
        "detail": "Download the .zip package from SkillVault and unzip it. The ci-cd-pipeline-builder/ folder contains SKILL.md plus any companion scripts, references and assets."
      },
      {
        "title": "Copy into your agent skills directory",
        "detail": "Move the folder into your agent's skills directory — e.g. ~/.claude/skills/ (Claude Code), .codex/skills/, .cursor/skills/ or your project's .claude/skills/ folder — then restart or reload the session."
      },
      {
        "title": "Use it",
        "detail": "Describe the task in natural language; the agent loads the skill automatically when the request matches the skill description."
      }
    ]
  },
  "usage": {
    "steps": []
  },
  "metadata": {
    "author": "SkillVault",
    "source": "https://skillvault.top/skills/ci-cd-pipeline-builder",
    "exported_at": "2026-11-03T07:45:13.423Z"
  }
}
ci-cd-pipeline-builder.aiskill (YAML)
format: aiskill/v1
skill:
  name: ci-cd-pipeline-builder
  slug: ci-cd-pipeline-builder
  version: 1.0.0
  description: >-
    Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline
    generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a
    new project, refactoring existing pipelines, or standardizing deployment workflows across
    multiple repos.
  category: Development
  tags:
    - engineering
  platforms:
    - chatgpt
    - claude-code
    - cursor
  tested_environment: >-
    Agent Skills convention (SKILL.md) — works with Claude Code, Cursor, ChatGPT/Codex and
    compatible agents
  license: MIT
prompts:
  system: "# CI/CD Pipeline Builder\r\n\r\n**Tier:** POWERFUL  \r\n**Category:** Engineering  \r\n**Domain:** DevOps / Automation\r\n\r\n## Overview\r\n\r\nUse this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages.\r\n\r\n## Core Capabilities\r\n\r\n- Detect language/runtime/tooling from repository files\r\n- Recommend CI stages (`lint`, `test`, `build`, `deploy`)\r\n- Generate GitHub Actions or GitLab CI starter pipelines\r\n- Include caching and matrix strategy based on detected stack\r\n- Emit machine-readable detection output for automation\r\n- Keep pipeline logic aligned with project lockfiles and build commands\r\n\r\n## When to Use\r\n\r\n- Bootstrapping CI for a new repository\r\n- Replacing brittle copied pipeline files\r\n- Migrating between GitHub Actions and GitLab CI\r\n- Auditing whether pipeline steps match actual stack\r\n- Creating a reproducible baseline before custom hardening\r\n\r\n## Key Workflows\r\n\r\n### 1. Detect Stack\r\n\r\n```bash\r\npython3 scripts/stack_detector.py --repo . --format text\r\npython3 scripts/stack_detector.py --repo . --format json > detected-stack.json\r\n```\r\n\r\nSupports input via stdin or `--input` file for offline analysis payloads.\r\n\r\n### 2. Generate Pipeline From Detection\r\n\r\n```bash\r\npython3 scripts/pipeline_generator.py \\\r\n  --input detected-stack.json \\\r\n  --platform github \\\r\n  --output .github/workflows/ci.yml \\\r\n  --format text\r\n```\r\n\r\nOr end-to-end from repo directly:\r\n\r\n```bash\r\npython3 scripts/pipeline_generator.py --repo . --platform gitlab --output .gitlab-ci.yml\r\n```\r\n\r\n### 3. Validate Before Merge\r\n\r\n1. Confirm commands exist in project (`test`, `lint`, `build`).\r\n2. Run generated pipeline locally where possible.\r\n3. Ensure required secrets/env vars are documented.\r\n4. Keep deploy jobs gated by protected branches/environments.\r\n\r\n### 4. Add Deployment Stages Safely\r\n\r\n- Start with CI-only (`lint/test/build`).\r\n- Add staging deploy with explicit environment context.\r\n- Add production deploy with manual gate/approval.\r\n- Keep rollout/rollback commands explicit and auditable.\r\n\r\n## Script Interfaces\r\n\r\n- `python3 scripts/stack_detector.py --help`\r\n  - Detects stack signals from repository files\r\n  - Reads optional JSON input from stdin/`--input`\r\n- `python3 scripts/pipeline_generator.py --help`\r\n  - Generates GitHub/GitLab YAML from detection payload\r\n  - Writes to stdout or `--output`\r\n\r\n## References\r\n\r\n- [references/pipeline-design-notes.md](references/pipeline-design-notes.md) — common pitfalls, best practices, detection heuristics, generation strategy, platform decision notes, pre-merge validation checklist, and scaling guidance\r\n- [references/github-actions-templates.md](references/github-actions-templates.md)\r\n- [references/gitlab-ci-templates.md](references/gitlab-ci-templates.md)\r\n- [references/deployment-gates.md](references/deployment-gates.md)\r\n- [README.md](README.md)"
  user_template: ""
variables: []
install:
  steps:
    - title: Download & unzip
      detail: >-
        Download the .zip package from SkillVault and unzip it. The ci-cd-pipeline-builder/ folder
        contains SKILL.md plus any companion scripts, references and assets.
    - title: Copy into your agent skills directory
      detail: >-
        Move the folder into your agent's skills directory — e.g. ~/.claude/skills/ (Claude Code),
        .codex/skills/, .cursor/skills/ or your project's .claude/skills/ folder — then restart or
        reload the session.
    - title: Use it
      detail: >-
        Describe the task in natural language; the agent loads the skill automatically when the
        request matches the skill description.
usage:
  steps: []
metadata:
  author: SkillVault
  source: https://skillvault.top/skills/ci-cd-pipeline-builder
  exported_at: "2026-11-03T07:45:13.423Z"

安装指南

  1. 1

    Download & unzip

    Download the .zip package from SkillVault and unzip it. The ci-cd-pipeline-builder/ folder contains SKILL.md plus any companion scripts, references and assets.

  2. 2

    Copy into your agent skills directory

    Move the folder into your agent's skills directory — e.g. ~/.claude/skills/ (Claude Code), .codex/skills/, .cursor/skills/ or your project's .claude/skills/ folder — then restart or reload the session.

  3. 3

    Use it

    Describe the task in natural language; the agent loads the skill automatically when the request matches the skill description.

使用方法

平台兼容性

ChatGPT GPTs

OpenAI

将系统提示词粘贴到 GPT 的「Instructions」字段,并把用户模板作为起始消息使用。

官方文档

Claude Code

Anthropic

将导出的 .aiskill JSON 保存为项目中的技能文件,或将系统提示词粘贴进 CLAUDE.md / 斜杠命令 Markdown 文件。

官方文档

Cursor

Anysphere

将系统提示词复制到 .cursor/rules/*.mdc(或设置中的 Project Rules),并在智能体提示词中引用用户模板。

官方文档

相关技能