Home / gke-labs / kube-agents · agents/platform/skills/gke-golden-path/SKILL.md · GitHub

gke-golden-path skillA

gke-golden-path is agent-read markdown (skill) from gke-labs/kube-agents: Provides GKE golden path configuration defaults, production readiness checklists, and cluster default patterns. Use when designing GKE clusters, verifying GKE production readiness, or checking configurations against GKE defaults. Don't use for setting up workload autoscaling specifically (use gke-workload-scaling instead)..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# GKE Golden Path Configuration

The golden path is the recommended Autopilot configuration for production
clusters. It defines sensible defaults — when the user requests different
settings, apply them and note relevant trade-offs.

> **MCP Tools:** `get_cluster`, `create_cluster`, `update_cluster`

## Rules

1.  **Default to the golden path.** Use golden path values unless the user
    requests otherwise. When deviating, note trade-offs but respect the user's
    choice.
2.  **Day-0 vs Day-1.** Flag Day-0 decisions (networking, private nodes,
    subnets, IP allocation) prominently — they are hard/impossible to change
    after creation.
3.  **Tool preference: MCP > gcloud > kubectl.** MCP is preferred as it directly
    interfaces with GKE APIs with structured data, reducing shell syntax errors
    and parsing ambiguities. See the `gke-basics` skill's CLI reference for full
    coverage matrix and override options. If the user
    says "use gcloud" or "use kubectl", respect that for the session.
4.  **Document decisions and rationale**, especially for Day-0 choices and
    golden path deviations.

## Required Inputs

If the user is unsure, use golden path defaults.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add gke-labs/kube-agents/gke-golden-path@git:20260807.d47bdf1
Exact content
mdr add gke-labs/kube-agents/gke-golden-path@sha256:cde697d895551233

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_jri7lx22r4ukfrka.svg)](https://markdownregistry.com/a/art_jri7lx22r4ukfrka)

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Versions

versioncommittedcommitsizeaudit
git:20260807.d47bdf1 latest2026-08-07 d47bdf1 6,039 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (6039 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

gke-labs/kube-agents · 64 stars · license Apache-2.0 · pushed 2026-09-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_jri7lx22r4ukfrka
GET https://markdownregistry.com/api/v1/resolve?ref=gke-labs/kube-agents/gke-golden-path
GET https://markdownregistry.com/api/v1/blob/cde697d8955512338969078944fe6d1306bc9a88251ac25914849d2fa7f3aa60

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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