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 Aarvion-AI/stackwise-skills --skill docker-expertgit clone --depth 1 https://github.com/Aarvion-AI/stackwise-skillsWrote 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/aarvion-ai/stackwise-skills/docker-expert)<a href="https://agentmods.dev/skills/aarvion-ai/stackwise-skills/docker-expert"><img src="https://agentmods.dev/badge/skills/aarvion-ai/stackwise-skills/docker-expert/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/aarvion-ai/stackwise-skills/docker-expert"><img src="https://agentmods.dev/badge/skills/aarvion-ai/stackwise-skills/docker-expert.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 | $0.00042 | $0.01285 |
| Opus 5 | $0.00021 | $0.00642 |
| Sonnet 5 | $0.00008 | $0.00257 |
| Haiku 4.5 | $0.00004 | $0.00128 |
Grade A, and why
docker-expert 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docker Expert
Build small, reproducible, non-root Docker images using Docker 27+ and BuildKit.
When to Use This Skill
- Creating or changing a
Dockerfile - Creating or debugging a
docker-compose.ymlorcompose.yaml - Converting a single-stage image into a multi-stage production image
- Improving Docker build cache behavior or BuildKit usage
- Adding
.dockerignore, health checks, or non-root execution - Diagnosing Docker image-size, startup, networking, volume, or Compose issues
Core Workflow
-
Inspect the runtime contract - identify the app start command, listening port, required files, environment variables, native dependencies, and health endpoint. Read existing Dockerfiles, Compose files, lockfiles, and
.dockerignorebefore making changes. -
Design build and runtime stages - separate build dependencies from runtime dependencies. Pin an explicit maintained base-image version, use named build stages, and copy only required runtime artifacts into the final image.
-
Implement Dockerfile and ignore rules - order layers from least frequently changed to most frequently changed: base image, OS packages, dependency manifests, dependency installation, then application source. Add
.dockerignorebefore relying onCOPY . .. -
Verify the image build - run
docker build --progress=plain -t app:local .; fix every reported issue and re-run until clean. Change only an application source file, rebuild, and confirm dependency installation is cached. -
Run the container - run
docker run --rm --name app-local -p 8080:8080 app:local, replacing8080with the real application port. Check logs withdocker logs app-local, verify the endpoint, fix failures, and re-run until clean. -
Implement Compose configuration when needed - use Compose for multi-service applications or local development. Define explicit services, ports, networks, volumes, health checks, and dependency readiness.
-
Verify Compose configuration - run
docker compose config; fix every reported issue and re-run until clean. Then rundocker compose up --build --wait, inspectdocker compose psanddocker compose logs, verify the application endpoint, and rundocker compose down --volumesafter testing.
What ships with it
3 files 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.
- 7d ago First seen · 117 lines · 42 tokens per session scan A 5ef121c3b84b
docker-expert is a skill published in the GitHub repository Aarvion-AI/stackwise-skills (5 stars, last pushed 2d ago), licensed MIT. It adds 42 tokens to every session and 1,285 once invoked, about $0.0002 per session on Opus 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 2026-09-04.
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