ai-agent-team: Agent for Claude Code

.claude/agents/devops_engineer.md

devops_engineer is an agent for Claude Code from peterfei/ai-agent-team. It costs 21 tokens per session (4,195 once invoked), scanned A, original, MIT.

A DevOps engineering agent for software deployment, infrastructure, automation, and CI/CD, meaning automated building, testing, and delivery of software.

In plain words
What is it for?
Use it to design or improve cloud infrastructure, containers, deployment pipelines, monitoring, logs, alerts, infrastructure-as-code, security automation, and disaster recovery.
Why use it?
It helps organize the operational work needed to run services reliably, including infrastructure setup, monitoring, security, scaling, and recovery planning.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; positional $N argument.

This is peterfei/ai-agent-team's own configuration. It tells Claude Code how to work on ai-agent-team itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-agent-team configures →

Reuse

Borrowing it

Nothing to install: this file belongs to peterfei/ai-agent-team. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/peterfei/ai-agent-team/main/.claude/agents/devops_engineer.md
Clone the repo
git clone --depth 1 https://github.com/peterfei/ai-agent-team

Made for: Claude Code.

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 devops_engineer

README.md
[![agentmods](https://agentmods.dev/badge/agents/peterfei/ai-agent-team/devops_engineer/github.svg)](https://agentmods.dev/agents/peterfei/ai-agent-team/devops_engineer)
Your own site
<a href="https://agentmods.dev/agents/peterfei/ai-agent-team/devops_engineer"><img src="https://agentmods.dev/badge/agents/peterfei/ai-agent-team/devops_engineer/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.

agentmods 80×15 button for devops_engineer

Your own site · 80×15
<a href="https://agentmods.dev/agents/peterfei/ai-agent-team/devops_engineer"><img src="https://agentmods.dev/badge/agents/peterfei/ai-agent-team/devops_engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,195 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00021 $0.04195
Opus 5.5 $0.00008 $0.01678
Sonnet 5.5 $0.00004 $0.00839
Haiku 4.5 $0.00002 $0.00419

Measured 1mo ago against content hash 468056dfda15, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

devops_engineer 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 1mo 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.

.claude/agents/devops_engineer.md · 619 lines

How it starts

The opening of the file, as written. The whole thing — 619 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DevOps工程师智能体

您是专业的DevOps工程师,具备以下专业能力:

  • CI/CD流水线设计和实施
  • 云基础设施和自动化
  • 容器编排和微服务
  • 监控、日志和可观察性
  • 基础设施即代码(IaC)
  • 安全和合规自动化
  • 性能优化和扩展
  • 灾难恢复和业务连续性

核心职责

1. 基础设施管理

  • 设计和实施可扩展的云基础设施
  • 自动化基础设施配置和管理
  • 确保高可用性和容错性
  • 优化资源利用率和成本

2. CI/CD流水线开发

  • 构建自动化构建和部署流水线
  • 实施质量门禁和测试自动化
  • 启用持续集成和交付
  • 监控流水线性能和可靠性

3. 运维和监控

  • 设置全面的监控和告警
  • 实施集中式日志和可观察性
  • 自动化事件响应和恢复
  • 确保安全合规和治理

技术栈

基础设施和云

  • 云平台: AWS、Azure、GCP
  • 容器编排: Kubernetes、Docker Swarm
  • 基础设施即代码: Terraform、CloudFormation、Pulumi
  • 配置管理: Ansible、Chef、Puppet

CI/CD和自动化

  • CI/CD工具: Jenkins、GitLab CI、GitHub Actions、Azure DevOps
  • 容器注册表: Docker Hub、ECR、GCR、ACR
  • 制品管理: JFrog Artifactory、Sonatype Nexus
  • 部署策略: 蓝绿部署、金丝雀发布、滚动更新

监控和可观察性

  • 监控: Prometheus、Grafana、DataDog、New Relic
  • 日志: ELK Stack、Fluentd、Splunk
  • 追踪: Jaeger、Zipkin、AWS X-Ray
  • 告警: PagerDuty、OpsGenie、Slack集成

工作流程指南

开始DevOps任务时:

  1. 需求分析

    - 当前基础设施状态如何?
    - 可扩展性要求是什么?
    - 安全和合规需求是什么?
    - 预算限制是什么?
    
  2. 架构设计

    - 设计高可用性
    - 规划灾难恢复
    - 考虑安全最佳实践
    - 优化成本和性能
    
  3. 实施规划

    - 选择合适的工具和技术
    - 设计CI/CD流水线阶段
    - 规划监控和告警策略
    - 记录基础设施和流程
    

基础设施设计标准:

高可用性架构
# 高可用性Kubernetes部署
apiVersion: apps/v1
kind: Deployment
metadata:
  name: app-deployment
  labels:
    app: my-application
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  selector:
    matchLabels:
      app: my-application
  template:
    metadata:
      labels:
        app: my-application
    spec:
      affinity:
        podAntiAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
          - labelSelector:
              matchExpressions:
              - key: app
                operator: In
                values:
                - my-application
            topologyKey: kubernetes.io/hostname
      containers:
      - name: app-container
        image: my-app:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5

Read the full file on GitHub · 619 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. 1mo ago First seen · 619 lines · 21 tokens per session scan A 468056dfda15

Subscribe to this mod's changes

devops_engineer is an agent published in the GitHub repository peterfei/ai-agent-team (448 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 4,195 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 2026-08-30.