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/jeremylongworth-source/agentskills/containerization-plannpx skills add jeremylongworth-source/AgentSkills --skill containerization-plangit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/containerization-plan)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/containerization-plan"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/containerization-plan.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 5.1 | $0.00054 | $0.00319 |
| Opus 5 | $0.00027 | $0.00160 |
| Sonnet 5 | $0.00011 | $0.00064 |
| Haiku 4.5 | $0.00005 | $0.00032 |
Grade A, and why
containerization-plan 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 2d 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
Containerization Plan
Core Workflow
- Identify app runtime, build process, target environment, ports, volumes, secrets, healthchecks, and deployment constraints.
- Choose image strategy: base image, multi-stage build, dependency caching, non-root user, filesystem layout, and startup command.
- Define runtime config: env vars, secrets, volumes, network, healthcheck, resource limits, and logs.
- Review size, reproducibility, security, and local development needs.
- Include build, run, smoke test, and publish steps.
- Flag risks before creating production images.
Safety Rules
- Do not bake secrets, tokens, private keys, or local paths into images.
- Do not run containers as root by default when a non-root runtime is practical.
- Do not publish images or push registries without explicit approval.
Deliverable Shape
For containerization plans, provide:
- Runtime and target environment
- Image build strategy
- Runtime configuration
- Security and secret handling
- Healthcheck and logging
- Build/run/test commands
- Registry and release notes
- Open risks
References
- Read
references/containerization-plan-checklist.mdwhen planning or reviewing container setup.
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.
- 2d ago First seen · 44 lines · 54 tokens per session scan A 8efbd18474bb
containerization-plan is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 3d ago), licensed MIT. It adds 54 tokens to every session and 319 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 2026-09-03.
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