containerization

containerization is a skill for Claude Code, Codex from arjunprabhulal/devops-skills. It costs 94 tokens per session (1,297 once invoked), scanned A, original, MIT.

A guide to packaging applications as small, repeatable, safer-to-run container images. Containers bundle an application with the files it needs to run.

In plain words
What is it for?
Writing Dockerfiles, using build stages and caching, configuring non-root users, and separating build-time files from runtime files.
Why use it?
It helps avoid slow rebuilds, oversized images, inconsistent environments, and applications running with unnecessary privileges.

Skill for Claude CodeCodex

Part of the devops-skills plugin — 56 skills shipped together

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.

agentmods
npx agentmods add skills/arjunprabhulal/devops-skills/containerization
Any agent
npx skills add arjunprabhulal/devops-skills --skill containerization
Clone the repo
git clone --depth 1 https://github.com/arjunprabhulal/devops-skills

Made for: Claude Code, Codex.

Or install devops-skills, the plugin that ships this one along with the rest of its 56 skills.

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 containerization

README.md
[![agentmods](https://agentmods.dev/badge/skills/arjunprabhulal/devops-skills/containerization.svg)](https://agentmods.dev/skills/arjunprabhulal/devops-skills/containerization)
Your own site
<a href="https://agentmods.dev/skills/arjunprabhulal/devops-skills/containerization"><img src="https://agentmods.dev/badge/skills/arjunprabhulal/devops-skills/containerization.svg" alt="Measured on agentmods" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,297 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00094 $0.01297
Opus 5 $0.00047 $0.00648
Sonnet 5 $0.00019 $0.00259
Haiku 4.5 $0.00009 $0.00130

Measured 3d ago against content hash 6aa4cd6fb3a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

containerization 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 3d 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.

skills/containers/containerization/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Containerization

A container image is a build artifact meant to be byte-identical everywhere it runs. Most Dockerfile trouble comes from treating it like a virtual machine — installing a shell's worth of tools, running as root, and rebuilding the world on every code change.

Aim for three properties: small, reproducible, and least-privileged. A change that does not move one of those is not worth making.

For language-specific multi-stage templates, distroless runtimes, and BuildKit cache and secret mounts, read references/dockerfile-patterns.md.

1. Order layers by how often they change

Docker caches per layer and invalidates every layer after the first change. Put the stable things first so a one-line edit does not re-download the internet:

COPY package.json package-lock.json ./
RUN npm ci                      # cached until dependencies change
COPY . .                        # invalidated on every source change

Copying source before installing dependencies means every code change reinstalls everything. This single reordering is usually the largest build-time win available.

Done when: a code-only change does not reinstall dependencies.

2. Separate build tooling from the runtime image

A multi-stage build compiles or installs in one stage and copies only the resulting artifact into a clean final stage. Compilers, headers, and package caches have no business shipping to production — they add size and give an attacker a toolbox if they land a shell. Name your stages (AS build, AS runtime) so the final COPY --from=build is unambiguous. Sizing the runtime image itself — which base to start the final stage from — is image-optimization's job; this step is about the boundary between building and running.

Done when: the runtime image contains no compiler, package manager cache, or source outside what running requires.

3. Pin the base image and run as a non-root user

FROM node:latest is not a build input, it is a random number generator — the tag moves under you and today's build is not tomorrow's. Pin to a digest or an explicit version tag so a rebuild six months from now produces the same bytes. Then drop privilege: create or reuse a non-root user and switch to it before the final CMD, so a container escape does not hand over root on the host. Combine this with a read-only root filesystem and a dropped CAP_* set where the runtime supports it.

Read the full file on GitHub · 108 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 3d ago First seen · 108 lines · 94 tokens per session scan A 6aa4cd6fb3a5

Subscribe to this mod's changes

containerization is a skill published in the GitHub repository arjunprabhulal/devops-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 94 tokens to every session and 1,297 once invoked, about $0.0005 per session on Opus 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.

Related

Other skills, from other repositories

google-mobile-ads-android-migrate-to-next-gen

Migrates Android applications from the old, legacy Google Mobile Ads (GMA) SDK (com.google.android.gms:play-services-ads) to the new GMA Next-Gen SDK (com.google.android.libraries.ads.mobile.sdk:ads-mobile-sdk). Provides comprehensive mapping tables for imports, classes, and method signatures to help determine…

google/skills · 105 tokens

agent-platform-inference

Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling…

google/skills · 144 tokens

agent-platform-deploy

Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a…

google/skills · 193 tokens

agent-platform-eval-flywheel

Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on…

google/skills · 108 tokens

agent-platform-tuning

Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use agent-platform-deploy), or managing serving endpoints (use agent-platform-endpoint-management).

google/skills · 64 tokens

agent-platform-alert-configuration

Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard…

google/skills · 143 tokens