Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agenticdevops/aoh --skill docker-disk-cleanupgit clone --depth 1 https://github.com/agenticdevops/aohWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agenticdevops/aoh/docker-disk-cleanup)<a href="https://agentmods.dev/skills/agenticdevops/aoh/docker-disk-cleanup"><img src="https://agentmods.dev/badge/skills/agenticdevops/aoh/docker-disk-cleanup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agenticdevops/aoh/docker-disk-cleanup"><img src="https://agentmods.dev/badge/skills/agenticdevops/aoh/docker-disk-cleanup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00207 |
| Opus 5.5 | $0.00013 | $0.00083 |
| Sonnet 5.5 | $0.00007 | $0.00041 |
| Haiku 4.5 | $0.00003 | $0.00021 |
Grade A, and why
docker-disk-cleanup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Docker Disk Cleanup
Overview
Diagnose Docker disk pressure before recommending cleanup. Prefer read-only inspection first and clearly separate safe recommendations from destructive commands.
Process
- Inspect Docker disk usage with
docker system df. - List stopped containers, dangling images, unused volumes, and builder cache.
- Explain what is consuming space.
- Recommend the smallest cleanup action that addresses the issue.
- Do not run destructive cleanup unless the active runtime explicitly supports approval and the user asks for it.
Helpful Commands
docker system df
docker ps -a --filter status=exited
docker images --filter dangling=true
docker volume ls
docker builder du
Deterministic Helper
Use scripts/inspect_docker_disk.sh when a repeatable read-only inspection is useful.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 33 lines · 33 tokens per session scan A dc3b0b96ec2e
docker-disk-cleanup is a skill published in the GitHub repository agenticdevops/aoh (6 stars, last pushed 3mo ago), licensed MIT. It adds 33 tokens to every session and 207 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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