devops-engineer

devops-engineer is an agent for Claude Code from hoangatg/ai-agent-toolkit. It costs 62 tokens per session (1,479 once invoked), scanned A, a copy of devops-engineer, MIT.

A specialist for deploying applications, managing servers, running CI/CD pipelines, and handling production operations.

In plain words
What is it for?
Use it to choose deployment platforms, deploy apps, manage services such as PM2, access servers over SSH, and plan rollbacks.
Why use it?
It provides a safety-focused process for high-risk changes such as releases, server access, and rollbacks.

Agent for Claude Code

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

Good fit Use it to choose deployment platforms, deploy apps, manage services such as PM2, access servers over SSH, and plan rollbacks.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/hoangatg/ai-agent-toolkit/devops-engineer
Install

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.

Clone the repo
git clone --depth 1 https://github.com/hoangatg/ai-agent-toolkit

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/hoangatg/ai-agent-toolkit/devops-engineer/github.svg)](https://agentmods.dev/agents/hoangatg/ai-agent-toolkit/devops-engineer)
Your own site
<a href="https://agentmods.dev/agents/hoangatg/ai-agent-toolkit/devops-engineer"><img src="https://agentmods.dev/badge/agents/hoangatg/ai-agent-toolkit/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/hoangatg/ai-agent-toolkit/devops-engineer"><img src="https://agentmods.dev/badge/agents/hoangatg/ai-agent-toolkit/devops-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,479 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 100% copy Near-identical to another mod 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 $0.00062 $0.01479
Opus 5.5 $0.00025 $0.00592
Sonnet 5.5 $0.00012 $0.00296
Haiku 4.5 $0.00006 $0.00148

Measured 1mo ago against content hash 21c0c2902876, 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.

Origin

This is a copy

100% identical to devops-engineer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agent/agents/devops-engineer.md · 243 lines

How it starts

The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DevOps Engineer

You are an expert DevOps engineer specializing in deployment, server management, and production operations.

⚠️ CRITICAL NOTICE: This agent handles production systems. Always follow safety procedures and confirm destructive operations.

Core Philosophy

"Automate the repeatable. Document the exceptional. Never rush production changes."

Your Mindset

  • Safety first: Production is sacred, treat it with respect
  • Automate repetition: If you do it twice, automate it
  • Monitor everything: What you can't see, you can't fix
  • Plan for failure: Always have a rollback plan
  • Document decisions: Future you will thank you

Deployment Platform Selection

Decision Tree

What are you deploying?
│
├── Static site / JAMstack
│   └── Vercel, Netlify, Cloudflare Pages
│
├── Simple Node.js / Python app
│   ├── Want managed? → Railway, Render, Fly.io
│   └── Want control? → VPS + PM2/Docker
│
├── Complex application / Microservices
│   └── Container orchestration (Docker Compose, Kubernetes)
│
├── Serverless functions
│   └── Vercel Functions, Cloudflare Workers, AWS Lambda
│
└── Full control / Legacy
    └── VPS with PM2 or systemd

Platform Comparison

Platform Best For Trade-offs
Vercel Next.js, static Limited backend control
Railway Quick deploy, DB included Cost at scale
Fly.io Edge, global Learning curve
VPS + PM2 Full control Manual management
Docker Consistency, isolation Complexity
Kubernetes Scale, enterprise Major complexity

Deployment Workflow Principles

The 5-Phase Process

1. PREPARE
   └── Tests passing? Build working? Env vars set?

2. BACKUP
   └── Current version saved? DB backup if needed?

3. DEPLOY
   └── Execute deployment with monitoring ready

4. VERIFY
   └── Health check? Logs clean? Key features work?

5. CONFIRM or ROLLBACK
   └── All good → Confirm. Issues → Rollback immediately

Read the full file on GitHub · 243 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 · 243 lines · 62 tokens per session scan A 21c0c2902876

Subscribe to this mod's changes

devops-engineer is an agent published in the GitHub repository hoangatg/ai-agent-toolkit (1 stars, last pushed 7mo ago), licensed MIT. It adds 62 tokens to every session and 1,479 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to devops-engineer, differing in 0 lines, and is treated as a copy.

Related

Other agents, from other repositories

clawteam-devops

DevOps task agent — automation-first, everything-as-code, shift-left security, metrics-driven feedback, small batches, chaos/antifragile; pipeline & deployment strategy frameworks, CI/CD maturity; delivery as engineered system.

deepelementlab/jupyter-studio · 51 tokens

clawteam-project-manager

PMO-style task agent — structured decomposition, constraint balance, proactive risk, communication as governance, rolling plans, value delivery; extended governance dimensions, lifecycle, cross-functional forums, EVM-style tracking.

deepelementlab/jupyter-studio · 46 tokens

clawteam-qa

QA task agent — shift-left quality built-in, risk-led strategy, test pyramid & quadrants, multi-dimensional coverage, testability, CI feedback, prevention over detection; strategy, design, metrics, validation, process gates.

deepelementlab/jupyter-studio · 51 tokens

clawteam-rnd-backend

Backend R&D task agent — layered abstraction, defensive coding, consistency-first data, built-in observability, evolvable design, perf/resource awareness; architecture layers, quality trade-offs, error taxonomy, distributed consistency patterns.

deepelementlab/jupyter-studio · 52 tokens

clawteam-rnd-frontend

Frontend R&D task agent — component model, declarative UI, data-driven flow, progressive enhancement, perf-first, a11y built-in; layered architecture, CSR/SSR/SSG/ISR, state taxonomy, RAIL-style optimization.

deepelementlab/jupyter-studio · 57 tokens

clawteam-rnd-mobile

Mobile R&D task agent — platform-first adaptation, resource constraints, offline-first, lifecycle-aware, privacy/security, store-safe delivery & hotfix; layered architecture, perf model, stack trade-offs, release pipeline.

deepelementlab/jupyter-studio · 49 tokens