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 fmind/dot --skill dockergit 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/docker)<a href="https://agentmods.dev/skills/fmind/dot/docker"><img src="https://agentmods.dev/badge/skills/fmind/dot/docker/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/fmind/dot/docker"><img src="https://agentmods.dev/badge/skills/fmind/dot/docker.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 | $0.00022 | $0.01013 |
| Opus 5.5 | $0.00009 | $0.00405 |
| Sonnet 5.5 | $0.00004 | $0.00203 |
| Haiku 4.5 | $0.00002 | $0.00101 |
Grade A, and why
docker 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docker and Container Runtime Management
Use docker, docker compose, and lazydocker to manage container execution, services, and local debugging. The containerize guide builds, publishes, and signs Python images; trivy scans them for vulnerabilities.
Docker, Compose, and Colima are host prerequisites; workstation tools do not install or start them. Inspect docker context ls before choosing a runtime and pass docker --context <context> on consequential commands; do not change the persistent default just to run a task. Container runs execute project code; reuse authority for the requested workload and resolve missing scope before running untrusted images or consequential workloads. Preserve existing volumes and containers.
Runtime Selection
- Linux: use the existing Docker-compatible engine; host daemon installation is outside user-space mise setup.
- macOS: use Colima instead of Docker Desktop; read colima for its context, socket, memory, and mount behavior.
Workflow
-
Verify daemon health and storage budget: confirm the daemon is responsive and check storage footprint before launching workloads. Run
dot doctor --headroombefore large pulls or builds.docker info --format 'Server={{.ServerVersion}} Driver={{.Driver}} Containers={{.Containers}} Images={{.Images}}' docker system df -
Manage Compose stacks: resolve the Compose file and project name first. Use a unique name for a new disposable stack; reuse an existing project's name only when operating that stack is in scope.
docker --context <context> compose -p <project> -f <compose-file> up -d docker --context <context> compose -p <project> -f <compose-file> ps docker --context <context> compose -p <project> -f <compose-file> logs --since 15m --tail 100 <service> docker --context <context> compose -p <project> -f <compose-file> down
What ships with it
6 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 fe53f28d8ac3
- 9d ago Changed · +2 lines · +7 tokens per session f82c36c26daa
- 11d ago Changed ed3d0eeb0947
- 12d ago Changed · -9 lines · -3 tokens per session ec99ec586e90
- 14d ago Changed · +1 lines 9b24b39a30e4
- 20d ago Changed · +1 lines 09a9d27282a8
- 23d ago Changed d604eed0a31f
- 28d ago Changed 070e22cf13f2
- 29d ago First seen · 77 lines · 18 tokens per session scan A fcb4f55ff955
docker is a skill published in the GitHub repository fmind/dot (11 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 1,013 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 2026-09-17.
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.
dotfiles-bootstrap
Bootstrap a workstation with the dotfiles framework. Takes a GitHub user / owner+repo / explicit clone URL and runs dot init (which shells out to chezmoi) with the right safety prompts. Honors the active agent profile (ask / plan / apply / audit) so it defaults to dry-run in safer modes and full apply in apply.