Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Wade-DevCode/awesome-coding-skills-cn --skill ci-cd-pipelinegit clone --depth 1 https://github.com/Wade-DevCode/awesome-coding-skills-cnWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wade-devcode/awesome-coding-skills-cn/ci-cd-pipeline)<a href="https://agentmods.dev/skills/wade-devcode/awesome-coding-skills-cn/ci-cd-pipeline"><img src="https://agentmods.dev/badge/skills/wade-devcode/awesome-coding-skills-cn/ci-cd-pipeline/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wade-devcode/awesome-coding-skills-cn/ci-cd-pipeline"><img src="https://agentmods.dev/badge/skills/wade-devcode/awesome-coding-skills-cn/ci-cd-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.02209 |
| Opus 5.5 | $0.00011 | $0.00884 |
| Sonnet 5.5 | $0.00005 | $0.00442 |
| Haiku 4.5 | $0.00003 | $0.00221 |
Grade A, and why
ci-cd-pipeline scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD 流水线
何时用
- 新建或修改任何 CI/CD 配置文件(GitHub Actions、GitLab CI、Jenkinsfile 等)。
- 流水线频繁失败、构建结果不一致、部署不可回滚时。
- 接入新项目或新环境时设计部署策略。
- 发现流水线中存在硬编码密钥或依赖隐式环境时。
核心规则
1. 阶段清晰,前序失败即停
规则: 流水线按 lint → test → build → deploy 顺序分阶段,每个阶段只做一件事;前序阶段失败,后续阶段不执行。
为什么: AI 生成的 CI 配置最常见的问题是把 lint、测试、构建、部署全塞进一个 job,或者测试失败后继续往生产部署。曾见过真实事故:测试报告里明确有失败用例,因为 YAML 里 continue-on-error: true 被随手加上,部署仍然执行,问题代码上了生产。
怎么做:
# GitHub Actions 示例
jobs:
lint:
runs-on: ubuntu-latest
steps: [...]
test:
needs: lint # ✅ 显式依赖,lint 失败即停
runs-on: ubuntu-latest
steps: [...]
build:
needs: test # ✅ 测试通过才构建
steps: [...]
deploy:
needs: build
if: github.ref == 'refs/heads/main' # ✅ 只部署 main 分支
steps: [...]
- 不加
continue-on-error: true,除非确实需要收集所有失败报告再决策。
2. 构建可重复:锁版本 + 缓存 + 产物带标识
规则: 锁定所有工具和依赖的版本;缓存依赖目录加速重复构建;构建产物打上版本标识(commit SHA 或语义版本),使每次构建可追溯。
为什么: AI 配置 CI 时倾向于用 npm install(不加 --frozen-lockfile)、不固定 Action 版本(uses: actions/checkout@main)、不给镜像打 tag。结果:同一份代码在不同时间构建出不同产物,线上出问题却无法精确定位是哪个版本,依赖每次都重新下载让构建平均耗时从 30 秒变成 5 分钟。
怎么做:
- uses: actions/setup-node@v4 # ✅ 固定 Action 版本
with:
node-version: '20'
cache: 'npm' # ✅ 启用依赖缓存
- run: npm ci # ✅ 使用 lockfile,拒绝版本漂移
- name: Build & tag image
run: |
IMAGE_TAG="${{ github.sha }}" # ✅ 用 commit SHA 作镜像标签
docker build -t myapp:${IMAGE_TAG} .
docker push myapp:${IMAGE_TAG}
3. 密钥走 secret store,最小权限
规则: 所有密钥、API token、部署凭据通过 CI 平台的 secret 机制注入,绝不硬编码进 YAML;为 CI 服务账号配置最小权限(只读仓库 + 只写目标服务),不用个人账号或 admin token。
为什么: AI 生成 CI 配置时极容易在 env: 块里直接写 AWS_SECRET_KEY: "AKIA..." 或在 run: 步骤里明文打印环境变量。这类配置一旦提交进公开仓库,密钥立刻面临泄露,且 git 历史删不干净。2023 年 GitHub 上每天有数千个 API key 因为这类配置被意外泄露。
怎么做:
- name: Deploy
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} # ✅ 引用 secret
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
run: aws s3 sync dist/ s3://my-bucket/
# ❌ 不要 run: echo $AWS_SECRET_ACCESS_KEY(日志会打印出来)
- IAM role / OIDC 优于长期密钥;部署账号只有目标环境的写权限,无法操作其他环境。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 200 lines · 27 tokens per session scan A 62956ba152c8
ci-cd-pipeline is a skill published in the GitHub repository Wade-DevCode/awesome-coding-skills-cn (7 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 2,209 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
ci-cd-pipeline compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ci-cd-pipelineWade-DevCode/awesome-coding-skills-cn | Skill | 7 | 5mo ago | MIT | A | 27 | Claude Code, Codex |
| chinese-git-workflowjnMetaCode/superpowers-zh | Skill | 8.5k | 2d ago | MIT | A | 69 | Claude Code |
| k6-load-testingfindscripter/everything-skills | Skill | 11 | today | none | A | 102 | Claude Code |
| ci-cd-pipeline-builderfindscripter/everything-skills | Skill | 11 | today | none | A | 118 | Claude Code |
| mise-toolchain-configuratorfindscripter/everything-skills | Skill | 11 | today | none | A | 119 | Claude Code |
| closed-loop-deliveryfindscripter/everything-skills | Skill | 11 | today | none | B | 164 | Claude Code |
| gitops-argocd-fluxfindscripter/everything-skills | Skill | 11 | today | none | D | 99 | Claude Code |