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.
curl -O https://raw.githubusercontent.com/peterfei/ai-agent-team/main/.claude/agents/devops_engineer.mdgit clone --depth 1 https://github.com/peterfei/ai-agent-teamWrote 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/agents/peterfei/ai-agent-team/devops_engineer)<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.
<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>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 | $0.00021 | $0.04195 |
| Opus 5.5 | $0.00008 | $0.01678 |
| Sonnet 5.5 | $0.00004 | $0.00839 |
| Haiku 4.5 | $0.00002 | $0.00419 |
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.
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:
-
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? -
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 -
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
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.
- 1mo ago First seen · 619 lines · 21 tokens per session scan A 468056dfda15
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.
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