Best AI Agent Skills for Docker and Containers 2026

People asking for "Docker agent skills" want one of two completely different things, and the two have almost nothing in common.

The first group wants the agent to write better Dockerfiles: correct layer ordering, real multi-stage builds, no secrets baked into an image. The second group wants the agent locked inside a container so a bad tool call can't reach their SSH keys.

Both are solved problems. They're solved by different repositories, and mixing them up is why people install something that doesn't do what they expected.

The options, split by which job they do

Star counts pulled from the GitHub API on 3 August 2026, except nanoclaw which is carried from our database. Skill counts and install steps came from each README.

Job one: teaching the agent Docker

Models write Dockerfiles that build. They write Dockerfiles that build badly. The common failures are consistent enough to be worth encoding: copying the whole source tree before installing dependencies so every code change busts the cache, running as root because nobody said not to, using latest tags, and leaving build-time secrets in a layer where docker history will find them.

Impertio-Studio/Docker-Claude-Skill-Package is the most focused answer. Twenty-two skills split across five directories: core covers architecture, security hardening, and networking; syntax covers Dockerfile instructions, BuildKit, multi-stage builds, Compose services, and CLI usage; impl covers build optimisation, production patterns, storage, CI/CD, and Go templates; errors covers build failures, runtime errors, networking problems, and Compose troubleshooting; agents holds two validation and generation skills.

The error-handling directory is the part I'd keep. Generation skills mostly duplicate what a good model does anyway. Debugging why a Compose network won't resolve a service name is where the specific knowledge pays.

At 9 stars this is a small project, so read the skill files before trusting them. They're short and MIT licensed.

akin-ozer/cc-devops-skills is broader and better maintained, with 285 stars and 31 skills. Docker is one section of it: dockerfile-generator, dockerfile-validator, plus helm-generator, helm-validator, k8s-yaml-generator, k8s-yaml-validator, and k8s-debug. Around it sit Terraform, Terragrunt, and Ansible generators and validators, eight CI/CD skills covering GitHub Actions, GitLab CI, Jenkins and Azure Pipelines, six observability skills for Fluent Bit, Loki, LogQL and PromQL, plus bash and Makefile tooling.

The generator-plus-validator pairing is the design decision worth copying. One skill writes the config, a separate one lints and security-checks it. That split means the agent can check its own output against a different set of rules than the ones it used to produce it.

Verified install, from the repo:

• /plugin marketplace add akin-ozer/cc-devops-skills
• /plugin install devops-skills@akin-ozer

Codex desktop users get a skills-only path:

• $skill-installer install https://github.com/akin-ozer/cc-devops-skills/tree/main/devops-skills-plugin/skills

If you already run Kubernetes, this pack replaces about four separate installs. Our Kubernetes skills roundup covers what to add beside it.

An install trap in the Docker package

The Impertio-Studio README documents its Claude Code install as a settings entry pointing at github:OpenAEC-Foundation/Docker-Claude-Skill-Package. The repository lives at Impertio-Studio/Docker-Claude-Skill-Package, and the GitHub API confirms it isn't a fork and has no parent record.

So the README references an org that isn't where the code sits. Either the project moved and the docs lagged, or the source string is simply wrong. Use the repository you can see:

• git clone https://github.com/Impertio-Studio/Docker-Claude-Skill-Package.git

Then reference the skills from skills/source/docker-*/.

This is the general case, not a one-off. Install strings in skill directories and in READMEs go stale faster than anything else in the ecosystem, and a wrong org in a config file fails in a way that looks like your setup is broken.

Job two: the container as blast radius

The other reason to care about Docker here has nothing to do with writing Dockerfiles. An agent with shell access can delete files, exfiltrate credentials, and push to remotes. A container is the cheapest boundary you can put around that.

agent-infra/sandbox is the serious option at 5,540 stars and Apache-2.0. It packs a browser, shell, filesystem, MCP support and a VS Code server into one Docker image, so the agent gets a full working environment that isn't yours. Point your agent at it and the worst case becomes a rebuilt container.

psyb0t/docker-claudebox takes a narrower angle: Claude Code inside Docker, exposed through five interfaces including an OpenAI-compatible API, an MCP server, a Telegram bot, and a CLI. Eighteen stars and a WTFPL licence tell you it's one person's tool rather than a supported product, but it was pushed on 1 August 2026 and the design is coherent. Useful if you want an agent reachable from your phone without giving it your laptop.

nanoclaw is the biggest project in this space by a distance, and containers are its security model rather than a feature. It connects to WhatsApp, Telegram, Slack, Discord and Gmail, keeps memory, and runs scheduled jobs, all inside containers.

Be clear about what the boundary covers. A container stops the agent from reading files you didn't mount and from writing outside its own filesystem. It does nothing about the network. By default a container can reach your LAN, your cloud metadata endpoint, and the whole internet, so an agent that has been talked into exfiltrating something can still do it. If that matters, put the container on an internal network with an egress allowlist and drop the metadata endpoint at the firewall.

Two settings cost nothing and are worth applying anyway: run the container read-only with a writable volume only where the agent needs to produce output, and set a memory and CPU limit so a runaway loop degrades one container instead of your machine.

The one thing that undoes all of it

Mounting the Docker socket.

Plenty of guides tell you to add /var/run/docker.sock to your container so the agent can manage other containers. That grants control of the Docker daemon, and the daemon runs as root on the host. An agent that can talk to the socket can start a privileged container mounting your entire filesystem. The container boundary you built is now decorative.

If the agent needs to orchestrate containers, use a rootless daemon or a socket proxy that allows only the specific API calls you need. If it doesn't, leave the socket out, which covers most cases.

Two smaller checks worth making. Don't pass your real credentials in as environment variables just because it's convenient; scope a token to the one repo the agent works in. And treat any skill that tells the agent to curl something and pipe it to a shell as an automatic no, regardless of star count.

What I'd install

For most developers: cc-devops-skills, because Docker rarely arrives alone and the same pack covers Kubernetes, Terraform, and CI. Add the Impertio error-handling skills if container debugging is a recurring cost.

For anyone letting an agent run unattended: agent-infra/sandbox, before any of the authoring skills. Getting a good Dockerfile out of a compromised laptop isn't a win.

Skip the tiny single-purpose Docker skill repos. There are a dozen with fewer than five stars, several last touched in 2025, and none do anything the two packs above don't cover.

For the wider workflow, our DevOps engineers roundup covers what sits alongside these, and the local and self-hosted AI guide is the natural next step if isolation is why you're here.

FAQ

What is the best Claude Code skill pack for Docker?

akin-ozer/cc-devops-skills, at 285 stars and Apache-2.0 licensed, covering dockerfile-generator, dockerfile-validator and k8s-debug alongside 28 other DevOps skills. For Docker-only depth, Impertio-Studio/Docker-Claude-Skill-Package ships 22 skills specifically for Dockerfile and Compose work.

Should I run my AI agent inside a Docker container?

Yes, if it has shell access and runs without you watching. agent-infra/sandbox packages a browser, shell, filesystem and VS Code server into one image at 5,540 stars. The container turns a bad tool call from a host compromise into a rebuild.

Is mounting the Docker socket into an agent container safe?

No. The Docker daemon runs as root on the host, so socket access lets a container start a privileged container that mounts your whole filesystem. Use a rootless daemon or a socket proxy with a restricted API allowlist, or leave the socket unmounted.

Why does the Docker skill package README point at a different GitHub org?

Its install config references OpenAEC-Foundation while the repository lives under Impertio-Studio, and the GitHub API confirms the repo is not a fork of anything. Clone from the org that hosts the code and ignore the source string in the README.

Do I need separate skills for Docker and Kubernetes?

Not if you use a combined pack. cc-devops-skills covers both, with seven skills across Dockerfile, Helm, Kubernetes YAML, and cluster debugging, which avoids running two overlapping installs that compete for context.