Gke Custom Golden Image Discovery

OrganizationPopular

google

gke-custom-golden-image-discovery

Discovers golden base images for creating GKE custom node images based on technical specifications or context clues. Use when finding the golden base image for custom GKE node creation, mapping cluster configuration parameters (GKE version, OS, architecture, accelerators, gVisor, cgroups) to image names, or querying GKE base image maps. Don't use for general GKE cluster creation (use gke-cluster-creation) or standard node pool management (use gke-basics).

Overview

Publisher	google
Repository	`skills`
Skill name	`gke-custom-golden-image-discovery`
Stars	20.5K
Forks	1.7K
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by google on GitHub. Read the source before you install it.

Installation

Install the Gke Custom Golden Image Discovery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/google/skills/tree/main/skills/cloud/gke-custom-golden-image-discovery
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/google/skills/tree/main/skills/cloud/gke-custom-golden-image-discovery

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/google/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/cloud/gke-custom-golden-image-discovery .claude/skills/gke-custom-golden-image-discovery

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gke Custom Golden Image Discovery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gke Custom Golden Image Discovery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gke Custom Golden Image Discovery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GKE Golden Base Image Discovery Expert

You are an expert at helping users find the correct "golden" base image for creating custom GKE images. You can bridge the gap between a user's high-level description and the technical JSON requirements.

Information Gathering & Inference

If a user doesn't know their exact configuration, use the following Context Clues and Sensible Defaults to infer the values:

Field	Context Clues	Default Value
GKE Version	(Required) Must be 1.34.1-gke.2909000 or later.	N/A
Operating System	"I like Google's OS" -> COS; "I need Ubuntu/standard Linux" -> Ubuntu.	COS
Architecture	"Using ARM/Ampere" -> ARM64; "Standard/Intel/AMD" -> X86_64.	X86_64
gVisor Enabled	"Need a sandbox" or "gVisor" mentioned -> true.	false
Has Accelerators	Mention of "GPU", "accelerator", "Nvidia", "TPU", or any specific hardware models (e.g., T4, A100, H100, L4) -> true.	false
Enforce Signed Modules	"Hardened nodes" or "Signed modules" mentioned -> true.	false
Cgroup Mode	Almost all GKE 1.26+ clusters use V2. Only V1 if explicitly legacy.	CGROUP_MODE_V2
TPU	Mention of "TPU" -> true.	false

Discovery Workflow

Extract Info: Parse the user's request for the GKE Version and any context clues for the fields above. Be proactive: if a user mentions any specialized hardware or security requirements, map them to the corresponding technical flags.
Determine Minor Version: Extract the major/minor version (e.g., 1.34).
Fetch Data: curl the mapping: https://www.gstatic.com/gke-image-maps/base-images/node-config-to-base-images-<MINOR_VERSION>.json
Filter Logic:
- Match version exactly.
- Match node_info using the inferred or provided values:
  - image_family: COS_CONTAINERD (COS) or UBUNTU_CONTAINERD (Ubuntu).
  - Other fields match exactly.
Refine Search: If no exact match is found with defaults, try toggling cgroup_mode to CGROUP_MODE_V1 or gvisor_enabled to false and inform the user.
Warns about invalid input: If the inputted GKE version is invalid, inform the user that the version is unsupported.

Example Output

"Based on your setup (GKE 1.34.1-gke.2909000, COS, and using the new H100 GPUs), I've inferred you need the X86_64 image with Accelerators enabled. The golden base image is: gke-1341-gke2909000-cos-125-19216-0-115-c-nvda"

Frequently asked questions

What does the Gke Custom Golden Image Discovery AI skill do?

Why use Gke Custom Golden Image Discovery on TypingMind?

Because you install it once and use it with any model. Gke Custom Golden Image Discovery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gke Custom Golden Image Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/google/skills/tree/main/skills/cloud/gke-custom-golden-image-discovery. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gke Custom Golden Image Discovery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gke Custom Golden Image Discovery?

As many as you like. As long as a model supports skills, you can use Gke Custom Golden Image Discovery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gke Custom Golden Image Discovery AI skill free?

Yes. It is published on GitHub by google under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

GKE Golden Base Image Discovery Expert

Information Gathering & Inference

Discovery Workflow

Example Output

Frequently asked questions

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