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/fmind/dot/containerizenpx skills add fmind/dot --skill containerizegit clone --depth 1 https://github.com/fmind/dotWrote 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/fmind/dot/containerize)<a href="https://agentmods.dev/skills/fmind/dot/containerize"><img src="https://agentmods.dev/badge/skills/fmind/dot/containerize.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 | $0.00040 | $0.01097 |
| Opus 5 | $0.00020 | $0.00549 |
| Sonnet 5 | $0.00008 | $0.00219 |
| Haiku 4.5 | $0.00004 | $0.00110 |
Grade A, and why
containerize 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 today.
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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Containerize an Application
Build a small, non-root, reproducible OCI image and verify it before it ships; cloud-run deploys it, trivy scans it, and cosign signs it.
Workflow
-
Go:
ko(default, no Dockerfile): builds a shell-less, multi-arch, reproducible image from a package path oncgr.dev/chainguard/static. Pin it per project (go get -tool github.com/google/ko, thengo tool ko).export KO_DOCKER_REPO=<registry>/<slug> go tool ko build ./cmd/<slug> --bare --platform=linux/amd64,linux/arm64 -
Python: multi-stage Dockerfile: copy Dockerfile and .dockerignore, then set the image digests and the
<slug>entry point. Other runtimes need their own lockfile-aware build stage.docker build -t <registry>/<slug>:<tag> . docker buildx build --platform linux/amd64,linux/arm64 -t <registry>/<slug>:<tag> --push . -
Wire the tasks into
mise.toml:build:imagebuilds,check:imagescans a local tarball so no registry push or digest is needed before the image ships.[env] KO_DOCKER_REPO = "<registry>/<slug>" # ko names images from it even when not pushing [tasks."build:image"] description = "Build the OCI image (ko)" run = "go tool ko build ./cmd/<slug> --bare" # or: docker build -t <registry>/<slug>:<tag> . [tasks."check:image"] description = "Scan the OCI image for vulnerabilities (trivy)" run = [ "mkdir -p tmp", "go tool ko build ./cmd/<slug> --bare --push=false --tarball tmp/image.tar", "trivy --config trivy.yaml image --input tmp/image.tar", ] -
Verify the pushed digest: use the registry digest for every scan, signature, SBOM, and deployment reference; scan per trivy, then sign, verify, and attest the SBOM per cosign.
-
Run locally the way Cloud Run will:
docker run --rm -p 8080:8080 -e PORT=8080 <registry>/<slug>@<digest>; a project with a local cluster pushes to its registry per k8s-local.
What ships with it
2 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.
- today Changed · -1 tokens per session 7ff7e9ab7959
- yesterday First seen · 67 lines · 41 tokens per session scan A 76515a9002bd
containerize is a skill published in the GitHub repository fmind/dot (4 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,097 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 2026-09-03.
Other skills, from other repositories
k8s-local
Create and manage local Kubernetes clusters (k3d or kind) and deploy to them with kubectl, helm, helmfile, and skaffold. Use for local k8s cluster setup, dev loops, and debugging.
cloud-run
Deploy container services to Google Cloud Run with Artifact Registry, keyless CI identity, Secret Manager, ko, or Dockerfiles.
security-scan
Scan repositories with Trivy and gitleaks for vulnerabilities, IaC, secrets, licenses, images, and git history; triage concrete findings.
containerize
Build minimal, non-root OCI images — ko for Go or a distroless multi-stage Dockerfile — then scan, sign, and SBOM them. Use when containerizing or packaging an app for deployment.
dot-cli
Use the dot CLI (fmind/dotfiles) to verify the environment, pull repos, manage the local k3d cluster, log agent sessions, and prune caches. Use when running or scripting any dot command.
go-stack
Build Go projects, libraries, CLIs, TUIs, web apps, or ADK agents with the standard package layout and pinned tooling.