agentleFS
frontier-ai-nextfrontier-ai-next/mgarlbot/skills/docker_deploy/SKILL.md

docker_deploy

Skill17 starsChanged 4 months agoMITView on GitHub

Inspect repo, author Dockerfile/compose, long builds, run with a clear deploy report

  • Reads credentials
  • Deletes or force-pushes

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 1 is distinctive, and 3 are 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.

  • 3

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Default chain: inspect project → artifacts → validate config → build (may take long) → detached run for daemons → report.

    line 11
  2. Very specific:

    If the user asks for apt / OS-level commands on a remote VPS, use skill vps_host_ssh (ssh -F /data/.ssh/config vps '...'), not local …

    line 15
  3. Very specific:

    Do not read or paste .env, keys, or tokens into the user-facing reply.

    line 19
  4. Very specific:

    Put real secrets in Dockerfile or print .env contents.

    line 33

≈ “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 / Compose (test or prod stack)

Default chain: inspect project → artifacts → validate config → build (may take long) → detached run for daemons → report.

Work inside the target project tree (relative paths, cd into the service directory). With HOST SHELL MODE you may use absolute paths to other project roots on this machine.

If the user asks for apt / OS-level commands on a remote VPS, use skill vps_host_ssh (ssh -F /data/.ssh/config vps '...'), not local compose unless they explicitly want local only.

Public URL, Traefik/Nginx/frp, and REG.RU DNS — skills ops_reverse_proxy and ops_dns_regru (inspect proxy on the VPS first, then config).

Do not read or paste .env, keys, or tokens into the user-facing reply.

Steps

  1. Analyze: language/runtime from pyproject.toml, package.json, go.mod, requirements.txt, existing Dockerfile; entrypoint (CMD), ports, env var names only (not secret values).
  2. Files: minimal working Dockerfile, sensible .dockerignore, docker-compose.yml if needed (build, ports, env_file: without baking secrets into the image).
  3. Config: docker compose config (or docker-compose config) — fix until clean.
  4. Build: docker compose build — iterate from logs; do not treat a long build as failure until the command exits with an error.
  5. Run: for APIs/web/daemons use docker compose up -d so the session does not block on foreground logs unless the user asks for attached logs.
  6. Verify: docker compose ps or docker ps --filter name=...; on failure docker compose logs --tail=80 <service>.
  7. Report: briefly what changed, service/container names, published ports, commands to verify and tail logs. State clearly e.g. “Deployed; check …”.

Do not

  • Put real secrets in Dockerfile or print .env contents.
  • Suggest rm -rf /, chmod-the-world, or destructive actions outside the task.

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.