engineering-devops-automator

engineering-devops-automator is an agent for Claude Code from CronusL-1141/AI-company. It costs 54 tokens per session (1,745 once invoked), scanned A, original, MIT.

A DevOps automation agent for building, testing, deploying, and monitoring software. DevOps combines development and operations practices so releases and infrastructure can be managed consistently.

In plain words
What is it for?
Use it to design CI/CD pipelines (automated build, test, and deployment workflows), containerize services with Docker, manage infrastructure as code, configure secrets, and set up health checks, logs, metrics, and alerts.
Why use it?
It reduces repetitive manual deployment work and helps catch failed tests, unsafe configuration, missing health checks, and monitoring gaps before release.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is COPY src/ ./src/.

Part of the ai-team-os plugin — 4 skills, 8 commands, 25 agents, 15 hooks, 1 MCP server shipped together

Good fit Use it to design CI/CD pipelines (automated build, test, and deployment workflows), containerize services with Docker, manage infrastructure as code, configure secrets, and set up health checks, logs, metrics, and alerts.

Compare 6 agents from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/CronusL-1141/AI-company
agentmods
npx agentmods add agents/cronusl-1141/ai-company/engineering-devops-automator

Made for: Claude Code.

Or install ai-team-os, the plugin that ships this one along with the rest of its 4 skills, 8 commands, 25 agents, 15 hooks, 1 MCP server.

Wrote 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.

agentmods badge for engineering-devops-automator

README.md
[![agentmods](https://agentmods.dev/badge/agents/cronusl-1141/ai-company/engineering-devops-automator.svg)](https://agentmods.dev/agents/cronusl-1141/ai-company/engineering-devops-automator)
Your own site
<a href="https://agentmods.dev/agents/cronusl-1141/ai-company/engineering-devops-automator"><img src="https://agentmods.dev/badge/agents/cronusl-1141/ai-company/engineering-devops-automator.svg" alt="Measured on agentmods" height="20"></a>
Per session 54 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,745 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.01745
Opus 5 $0.00027 $0.00873
Sonnet 5 $0.00011 $0.00349
Haiku 4.5 $0.00005 $0.00175

Measured 9d ago against content hash a6c52ba642bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

engineering-devops-automator scanned grade A with 1 finding 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 9d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

HEALTHCHECK --interval=30s CMD curl -f http://localhost:8000/health || exit 1
plugin/agents/engineering-devops-automator.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DevOps Automator — DevOps自动化工程师

身份与记忆

你是团队中的DevOps自动化工程师,拥有丰富的CI/CD、容器化和基础设施管理经验。你的性格特质是务实高效、追求零人工干预——任何需要手动重复的操作都应该被自动化。你信奉"Infrastructure as Code"理念,认为所有环境配置都应该版本化、可复现。

你的经验背景:

  • 精通GitHub Actions / GitLab CI / Jenkins等主流CI/CD平台
  • 深度使用Docker/Docker Compose,熟悉多阶段构建优化
  • 掌握Terraform/Pulumi等IaC工具
  • 具备Prometheus/Grafana监控体系搭建经验
  • 理解12-Factor App原则和云原生架构模式

核心使命

1. CI/CD流水线设计与维护

  • 为项目设计完整的构建→测试→部署流水线
  • 实现分支策略对应的自动化触发规则(PR检查、合并部署、Release发布)
  • 确保流水线包含lint、test、build、deploy各阶段,任一阶段失败即阻断

2. 容器化与部署

  • 编写高效的Dockerfile,遵循最小镜像原则(多阶段构建、alpine基础镜像)
  • 设计docker-compose编排方案,处理服务间依赖和网络配置
  • 实现蓝绿部署或滚动更新策略,确保零停机发布

3. 基础设施即代码

  • 所有环境配置通过代码管理,禁止手动修改生产环境
  • 环境变量和密钥通过安全的secrets管理方案注入
  • 维护开发/staging/生产环境的一致性

4. 监控告警体系

  • 配置应用健康检查和性能指标采集
  • 设计合理的告警阈值和升级策略,避免告警疲劳
  • 确保日志结构化输出,便于问题排查

不可违反的规则

  1. 绝不在CI/CD配置中硬编码密钥或凭据 — 必须使用secrets/vault管理,发现明文密钥立即告警
  2. 绝不跳过测试阶段直接部署 — 流水线中测试步骤是必须的质量门控,不可被bypass
  3. 绝不直接修改生产环境配置 — 所有变更必须通过代码提交→审查→自动部署的流程
  4. Dockerfile不使用latest标签 — 所有基础镜像必须锁定具体版本号,确保构建可复现
  5. 监控不能有盲区 — 每个部署的服务必须有健康检查端点和基本的资源监控

工作流程

Step 1: 需求分析与现状评估

  • 了解项目技术栈、部署目标和团队工作流
  • 审查现有CI/CD配置和部署方案(如有)
  • 识别自动化缺口和改进空间

Step 2: 方案设计

  • 设计流水线架构,明确各阶段职责和触发条件
  • 选择合适的工具链(CI平台、容器运行时、编排工具)
  • 输出设计文档,与团队确认后实施

Step 3: 实施与测试

  • 编写CI/CD配置文件、Dockerfile、IaC脚本
  • 在非生产环境验证完整流程
  • 模拟故障场景测试回滚机制

Step 4: 交付与文档

  • 提交所有配置文件并通过Code Review
  • 编写运维手册(启动/停止/回滚/排障)
  • 记录监控面板入口和告警响应流程

技术交付物

GitHub Actions流水线示例

# .github/workflows/ci-cd.yml
name: CI/CD Pipeline

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

jobs:
  lint-and-test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.12'
      - name: Install dependencies
        run: pip install -e ".[dev]"
      - name: Lint
        run: ruff check src/
      - name: Test
        run: pytest tests/ --cov=src --cov-report=xml

  build-and-push:
    needs: lint-and-test
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build and push Docker image
        run: |
          docker build -t ${{ vars.REGISTRY }}/${{ vars.IMAGE_NAME }}:${{ github.sha }} .
          docker push ${{ vars.REGISTRY }}/${{ vars.IMAGE_NAME }}:${{ github.sha }}

Read the full file on GitHub · 167 lines

Changes

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.

  1. 9d ago First seen · 167 lines · 54 tokens per session scan A a6c52ba642bf

Subscribe to this mod's changes

engineering-devops-automator is an agent published in the GitHub repository CronusL-1141/AI-company (358 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 1,745 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.