A guide to building, storing, and using container images on Control Plane. A container image is a packaged application and its dependencies; a registry stores those images for deployment.

Use it to build images locally or remotely, push them to the private registry, manage tags and digests, and configure pull secrets for private images.

It removes the need to manage every image step locally and helps diagnose incorrect image references, incompatible images, and missing permissions.

image — Skill by controlplane-com

Install

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.

agentmods

npx agentmods add skills/controlplane-com/ai-plugin/image

Any agent

npx skills add controlplane-com/ai-plugin --skill image

Clone the repo

git clone --depth 1 https://github.com/controlplane-com/ai-plugin

Made for: Claude Code, Codex.

Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,631 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00053	$0.04631
Opus 5	$0.00026	$0.02315
Sonnet 5	$0.00011	$0.00926
Haiku 4.5	$0.00005	$0.00463

Measured 2d ago against content hash 84309f89ab24, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

image 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.

plugins/cpln/skills/image/SKILL.md · 164 lines

How it starts

The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Control Plane Images

Tool availability: some MCP tools named here live in the full toolset profile — if one is not advertised on this connection, tell the user to reconnect the MCP server with ?toolsets=full (or use the cpln CLI fallback). Reads work on every profile via the generic list_resources / get_resource tools; delete_resource is on every profile except readonly.

Every org gets a private registry at ORG.registry.cpln.io — a standard Docker registry (docker login/push/pull/search all work). Pushing a tag automatically creates an image resource named NAME:TAG in the org (read-only repository, tag, digest, manifest fields; only metadata tags are editable). An image resource is never created directly — POST /org/ORG/image returns 403 "You can create an image only by pushing" — but a build can run on Control Plane instead of local Docker (cpln image build --remote), which is the answer whenever there is no Docker daemon. The recurring failures are a wrong reference form, a non-linux/amd64 image (exec format error), and a missing or mismatched pull secret.

Image references

Source	Reference in workload spec	Pull secret
Your org's registry (preferred)	`//image/NAME:TAG` (long form `/org/ORG/image/NAME:TAG`)	No — automatic
Your org's registry (hostname form)	`ORG.registry.cpln.io/NAME:TAG` — the API rewrites it to the link form on write	No — automatic
Another Control Plane org	`OTHER-ORG.registry.cpln.io/NAME:TAG` — stays a literal external reference	Yes (`docker`)
Public registry	Exact string: `nginx:latest`, `ghcr.io/owner/app:v1` — never add a `docker.io/` prefix	No
Private external registry (ECR, GCR/GAR, private Docker Hub, ACR...)	Full host path, e.g. `ACCOUNT.dkr.ecr.REGION.amazonaws.com/app:v1`	Yes

"Image name" always includes the tag (my-app:v1.0); a missing tag means :latest. Name and tag each max 128 chars; at most two : (the second only for a registry port); digest pinning NAME@sha256:HEX is supported.
Link references (/...) must point into the same org — other orgs are reached only via their registry hostname, which is why they need a pull secret.

Read the full file on GitHub · 164 lines

Changes

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 · 164 lines · 53 tokens per session scan A 84309f89ab24

Subscribe to this mod's changes

image is a skill published in the GitHub repository controlplane-com/ai-plugin (10 stars, last pushed 8d ago), licensed MIT. It adds 53 tokens to every session and 4,631 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.

DevOps and cloud ai ai-agents claude-code cloud-native codex controlplane

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