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 agentmods add skills/anthonyposchen/agent-skills/dockerfilenpx skills add AnthonyPoschen/agent-skills --skill dockerfilegit clone --depth 1 https://github.com/AnthonyPoschen/agent-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/anthonyposchen/agent-skills/dockerfile)<a href="https://agentmods.dev/skills/anthonyposchen/agent-skills/dockerfile"><img src="https://agentmods.dev/badge/skills/anthonyposchen/agent-skills/dockerfile.svg" alt="Measured on agentmods" 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 | $0.00068 | $0.00802 |
| Opus 5 | $0.00034 | $0.00401 |
| Sonnet 5 | $0.00014 | $0.00160 |
| Haiku 4.5 | $0.00007 | $0.00080 |
Grade A, and why
dockerfile 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 3d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dockerfile
Goal
Create Dockerfiles that are secure, reproducible, and useful as the canonical local CI build. Prefer multi-stage builds unless the user explicitly asks for a single-stage file.
Decision Order
- Identify the final runtime artifact.
- If the output is a single static binary, aim for a
scratchfinal image. - If the output needs an interpreter, shared libraries, package files, or
runtime dependencies, aim for an Alpine final image such as
python:<version>-alpine,node:<version>-alpine, or plainalpine. - If Alpine is incompatible with required native dependencies, explain why and choose the smallest appropriate runtime base.
- Keep build tools, test tools, package managers, and source code out of the final image unless they are required at runtime.
Required Container Policy
- Add
ARG UID=10001andARG GID=10001in every stage that creates or owns files used by the runtime image. - Run the final container as non-root with
USER ${UID}:${GID}or a named user created from those args. - Ensure every file used by the final executable is owned by the runtime UID/GID.
Prefer
COPY --chown=${UID}:${GID}for final-stage copies. - For
scratch, use numericUSER ${UID}:${GID}and copy only required files: the static binary, CA certificates when outbound TLS is needed, and any minimal config/data files the binary actually reads. - For Alpine runtime images, create the user/group from
UIDandGID, then copy application files with that owner. - Set a narrow
WORKDIR; do not run from filesystem root. - Use exec-form
ENTRYPOINTorCMD.
Build And Test Pattern
- Use a dedicated build stage for compilation, dependency installation, and generated artifacts.
- Add a test stage when the project has a clear test command. Examples:
go test ./...,cargo test --locked,npm test,pytest. - Make the default Docker build exercise tests when practical by having the
production stage depend on the tested artifact path, or document:
docker build --target test .. - Keep the Dockerfile sufficient for local CI verification so GitHub Actions can
usually be a simple
docker buildplus optional image push. - Use BuildKit cache mounts when they improve repeat builds and the project already assumes BuildKit.
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.
- 3d ago First seen · 80 lines · 68 tokens per session scan A ebbc25c95743
dockerfile is a skill published in the GitHub repository AnthonyPoschen/agent-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 68 tokens to every session and 802 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…