Docker Management logo

Docker Management

Organization
taracodlabs
docker-management

Docker containers, images, volumes, networks (CLI + Dockerode)

Overview

Publishertaracodlabs
Repositoryaiden
Skill namedocker-management
Stars
852
Forks
150
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by taracodlabs on GitHub. Read the source before you install it.

Installation

Install the Docker Management AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/taracodlabs/aiden/tree/main/skills/docker-management
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/taracodlabs/aiden.git /tmp/aiden
mkdir -p .claude/skills
cp -r /tmp/aiden/skills/docker-management .claude/skills/docker-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docker Management in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Docker Management on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Docker Management is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Docker Container Management

Manage Docker containers, images, volumes, and networks using the Docker CLI or Dockerode (Node.js Docker API client already in DevOS).

When to Use

  • User wants to list running or stopped containers
  • User wants to start, stop, or restart a container
  • User wants to pull, build, or remove Docker images
  • User wants to view container logs
  • User wants to inspect container resource usage

How to Use

1. List containers

powershell
# Running containers
docker ps

# All containers including stopped
docker ps -a --format "table {{.Names}}\t{{.Status}}\t{{.Image}}\t{{.Ports}}"

2. Start, stop, and restart containers

powershell
docker start  my-container
docker stop   my-container
docker restart my-container

# Stop all running containers
docker stop $(docker ps -q)

3. View container logs

powershell
# Last 100 lines
docker logs my-container --tail 100

# Follow live output
docker logs my-container --follow --tail 50

4. Manage images

powershell
# List images
docker images

# Pull latest image
docker pull nginx:latest

# Remove image
docker rmi nginx:latest

# Build from Dockerfile in current directory
docker build -t my-app:v1 .

5. Container resource usage

powershell
# Live resource stats (CPU, memory, network)
docker stats --no-stream

# Inspect a specific container
docker inspect my-container | python -m json.tool

6. Manage volumes and networks

powershell
# List volumes
docker volume ls

# List networks
docker network ls

# Remove unused volumes (reclaim disk)
docker volume prune -f

# Remove stopped containers, unused images, and networks
docker system prune -f

7. Execute commands inside a container

powershell
# Interactive shell
docker exec -it my-container /bin/bash

# Run a single command
docker exec my-container cat /etc/nginx/nginx.conf

8. Docker Compose operations

powershell
# Start all services defined in docker-compose.yml
docker compose up -d

# View logs for all services
docker compose logs -f

# Stop and remove containers
docker compose down

# Rebuild and restart a specific service
docker compose up -d --build api

9. Use Dockerode API (Node.js)

javascript
// Already available in DevOS dependencies
const Dockerode = require('dockerode')
const docker    = new Dockerode()

const containers = await docker.listContainers({ all: true })
containers.forEach(c => console.log(c.Names[0], c.State, c.Image))

const container = docker.getContainer('my-container')
await container.restart()
console.log('Restarted')

Examples

"Show me all running containers and their ports" → Use step 1 with docker ps and the format string.

"The nginx container seems slow — show me its CPU and memory usage" → Use step 5 with docker stats --no-stream filtered to the nginx container.

"Rebuild and restart the API service after my code change" → Use step 8: docker compose up -d --build api.

Cautions

  • docker system prune removes ALL stopped containers, unused images, and networks — confirm with the user first
  • docker stop $(docker ps -q) stops ALL running containers — confirm which containers to stop
  • Bind mounts expose host filesystem paths to containers — check paths before mounting
  • For production deployments, prefer docker compose or Kubernetes over direct docker run commands
  • Container logs can grow very large — use --tail to limit output for inspection

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Docker Management AI skill do?

Docker containers, images, volumes, networks (CLI + Dockerode)

Why use Docker Management on TypingMind?

Because you install it once and use it with any model. Docker Management is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Docker Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/taracodlabs/aiden/tree/main/skills/docker-management. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Docker Management?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Docker Management?

As many as you like. As long as a model supports skills, you can use Docker Management with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Docker Management AI skill free?

Yes. It is published on GitHub by taracodlabs under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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