Docker disk cleanup

Skill jimtin/production-ai/skills/docker-disk-cleanup

Skills and guardrails that make AI coding agents prove their work: planning gates, test preflights, fail-closed deployment, and a self-improving skill library.

Install

npx -y skills add jimtin/production-ai --skill docker-disk-cleanup

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Conservative Docker-native disk cleanup for developer machines and local PR-gate hosts. Use when asked to clean Docker disk usage, reclaim Docker image/build-cache/volume space, run daily Docker cleanup, diagnose Docker disk pressure, or safely prune containers, networks, images, BuildKit cache, and unused volumes while preserving active services and gate work.

SKILL.md

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Docker Disk Cleanup

Purpose

Use this skill to reclaim Docker disk space without damaging active local services, test databases, or PR-gate runs. Prefer the bundled script over ad hoc prune commands.

Operating Rules

Start with an audit: filesystem free space, docker info, docker system df, containers, and volumes.
Use scripts/docker-disk-cleanup.mjs; do not hand-roll prune order unless the script is missing or cannot run.
Do not use sudo.
Do not delete named project volumes manually. Let Docker remove only volumes it reports as dangling, after attachment checks.
Do not run overlapping cleanup jobs. The script uses a lock in the report directory.
Preserve active services. If gate-like containers are running, or the user says a gate is active, run active-gate mode so image and builder pruning use an age filter.
Treat Docker race errors such as containers disappearing between list and prune as recheck-and- continue signals unless the script reports a hard failure.
Keep reports sanitized: do not print env values, tokens, auth files, or secret-looking strings.

Quick Start

Run a dry run first:

node ~/.codex/skills/docker-disk-cleanup/scripts/docker-disk-cleanup.mjs audit
node ~/.codex/skills/docker-disk-cleanup/scripts/docker-disk-cleanup.mjs cleanup --dry-run

Run cleanup:

node ~/.codex/skills/docker-disk-cleanup/scripts/docker-disk-cleanup.mjs cleanup

For a known active PR gate or long validation run:

node ~/.codex/skills/docker-disk-cleanup/scripts/docker-disk-cleanup.mjs cleanup --active-gate-mode

When volume risk is unclear:

node ~/.codex/skills/docker-disk-cleanup/scripts/docker-disk-cleanup.mjs cleanup --skip-volumes

Workflow

Confirm the target path. Probe the filesystem that actually holds Docker data or the active workspace. Pass it with --workspace <path> or set DOCKER_DISK_CLEANUP_WORKSPACE. If unsure, use the current working directory and say so.
Audit first. Run audit or cleanup --dry-run. Read docker system df before deciding how aggressive cleanup should be.
Check active work. Inspect running containers and the script's activeGateMode decision. Use --active-gate-mode when a PR gate, test gate, or build is active.
Run serialized cleanup. The script plans commands in this order:
- docker container prune -f
- docker network prune -f
- docker image prune -a ... -f
- docker builder prune -a ... -f
- dangling volume attachment checks
- docker volume prune -a -f when supported, otherwise docker volume prune -f
- final docker image prune -a ... -f
Report the outcome. Include initial/final disk usage, Docker usage, mode, commands run, report path, removed-space summary when Docker provides one, skipped steps, and blockers.

Daily Automation Contract

A daily cleanup automation should run:

node ~/.codex/skills/docker-disk-cleanup/scripts/docker-disk-cleanup.mjs cleanup --workspace <workspace-path>

Use a report directory under the local agent home, for example:

--report-dir ~/.codex/automations/daily-docker-cleanup

Schedule dry runs first when moving the automation to a new machine.

Safety Policy

Read references/safety-policy.md before changing cleanup behavior, adding new destructive operations, or adapting the skill to a non-Docker-Desktop host.

The threat model lives in docker-disk-cleanup-threat-model.md; review it before publishing changes to cleanup behavior, report sinks, or scheduler integration.

Completion Blockers

Cleanup ran without a prior audit or dry-run-level evidence.
A second cleanup was launched while one was already running.
Active gate work was detected but broad image/build-cache pruning ran without an age filter.
Volumes were deleted manually by name instead of through Docker's unused-volume prune with attachment checks.
The report omits skipped steps, blockers, or whether active-gate mode was used.
Secret material or local auth paths were printed in a report or chat response.