agentleFS
liutaosliutaos/ops-skills/skills/docker-ops/docker-container/SKILL.md

docker-container

Skill0 starsChanged 51 days agoMITView on GitHub

Docker container lifecycle management (run / stop / rm / exec / logs). Use when: starting/stopping containers, exec-ing into a container, or viewing logs; rm -f goes through second confirmation. Boundary: authorized hosts only.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    remove requires a forced second confirmation (avoid deleting a running service by mistake)

    line 18
  2. Very specific:

    Run docker commands via shell-exec.

    line 22

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

docker-container

Capabilities

  • Container start / stop / restart / remove
  • Container log viewing
  • Concurrent multi-container operations

Safety gate

  • remove requires a forced second confirmation (avoid deleting a running service by mistake)
  • Log operations

EXECUTION (real engine)

Run docker commands via shell-exec.

opsctl shell-exec --host web1 --cmd "docker ps -a" --mode auto
opsctl shell-exec --host web1 --cmd "docker run -d --name web -p 80:80 nginx" --mode yes
opsctl shell-exec --host web1 --cmd "docker rm -f web" --mode yes

docker rm -f is a forced delete and goes through gate second confirmation.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.