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OpenClaw skill

docker-essentials

An OpenClaw skill that provides agents with tools to manage Docker containers, images, volumes, and networks. It includes commands such as docker ps, docker images, docker run, docker volume ls, and docker network ls. The skill enables essential Docker operations directly within agent workflows.

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How this skill works

  • The skill accepts natural language tasks describing Docker operations
  • It classifies the task into one of five actions: pull, run, ps, stop, or rm
  • It extracts required parameters such as image name, container name, and options from the task
  • It constructs and executes the corresponding Docker CLI command
  • It captures the command's stdout, stderr, and exit code
  • It returns a JSON object containing success status, message, and output

When to use it

  • When listing running or all Docker containers
  • When listing available Docker images
  • When pulling a Docker image from a registry
  • When building a Docker image from a Dockerfile
  • When running a new Docker container from an image
  • When stopping a running Docker container
  • When removing a stopped Docker container
  • When executing a command inside a running Docker container
  • When listing Docker volumes
  • When creating a Docker volume

Best practices

  • Install Docker and ensure the daemon is running before using the skill
  • Verify Docker CLI is accessible from the PATH
  • Use `docker_stop` before `docker_rm` for graceful container shutdown
  • Check for port conflicts before using `docker_run` with port mappings

Example use cases

  • Pulling a Docker image: Pulls the nginx Docker image using docker_pull('nginx').
  • Running an Nginx container: Runs an nginx container with port mapping using docker_run('nginx', ports='80:80').
  • Listing running containers: Lists currently running Docker containers using docker_ps().
  • Stopping a container: Stops a specific Docker container by ID using docker_stop('abc123').
  • Viewing container logs: Retrieves logs from a specific Docker container using docker_logs('abc123').

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