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google/gke-basics

google

gke-basics

Core GKE cluster discovery and hub. Use to route to specialized GKE skills. Do not use for specialized tasks (networking, security, etc.) directly.

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category:Containers
New~983
v2.0Saved Jun 28, 2026

GKE Basics

Managed Kubernetes platform on Google Cloud. Defaults to Autopilot mode.

Quick Start

gcloud services enable container.googleapis.com --quiet
gcloud container clusters create-auto my-cluster --region=us-central1 --quiet
gcloud container clusters get-credentials my-cluster --region=us-central1 --quiet

GKE Skill Routing Table

Load the single, most specific GKE sub-skill below matching your workload requirements. Do not load multiple GKE skills unless explicitly required.

Scenario Trigger Keywords Target Skill
Golden Path Defaults production defaults, golden gke-golden-path
: : path : :
Cluster Creation create cluster, provision gke-cluster-creation
: : GKE : :
Networking & Ingress private cluster, VPC, gke-networking
: : Gateway API, Ingress, DNS : :
Security & IAM Workload Identity, Secret gke-security
: : Manager, RBAC, hardening : :
Autoscaling HPA, VPA, Cluster gke-scaling
: : Autoscaler, NAP : :
Compute Classes ComputeClass, Spot fallback, gke-compute-classes
: : GPU/TPU nodes : :
Cost Optimization Spot VMs, rightsizing, cost gke-cost
: : allocation : :
AI/ML Workloads LLM, GPU/TPU inference, gke-inference
: : serving, vLLM : :
Cluster Upgrades upgrade, maintenance window, gke-upgrades
: : release channel : :
Observability monitoring, logging, gke-observability
: : Prometheus, dashboards : :
Multi-tenancy namespace isolation, gke-multitenancy
: : resource quota, LimitRange : :
Batch & HPC batch, HPC, Kueue, JobSet, gke-batch-hpc
: : parallel jobs : :
App Onboarding containerize, Dockerfile, gke-app-onboarding
: : deploy app, onboard : :
Backup & DR backup plan, restore, gke-backup-dr
: : disaster recovery, CMEK : :
Storage & PVC SSD, PV, PVC, StorageClass, gke-storage
: : GCS FUSE : :
Reliability PDB, health probe, liveness, gke-reliability
: : readiness : :

Conceptual & Informational Queries (CRITICAL)

For purely conceptual, educational, or informational questions (e.g. "What is GKE?", "Explain GKE architecture", or "Compare Standard vs Autopilot" in a generic sense):

  • Rule: Answer immediately using your pre-trained knowledge.
  • Constraint: Do not execute code searches, directory listings, or other tool calls unless the user explicitly requests you to inspect the local workspace or run a command. Keep it fast, cheap, and direct.
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Overall Score

81/100

Grade

B

Good

Safety

82

Quality

82

Clarity

85

Completeness

75

Summary

The GKE Basics skill is a discovery and routing guide that directs users to specialized GKE sub-skills based on their workload requirements. It provides quick-start commands, a comprehensive routing table matching scenarios to specific skills, and supporting reference documentation covering CLI tools, MCP server usage, core GKE concepts, IaC patterns, and client libraries. The skill explicitly advises against using it directly for specialized tasks and prioritizes routing over hands-on instruction.

Static Analysis Findings

1 finding

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Command Injection
SEC-011Dynamic Shell Eval

Shell eval/exec of dynamic content

references/cli-reference.mdexec`

Detected Capabilities

shell execution (gcloud, kubectl commands)code examples (Bash, HCL, Python, Go, JavaScript, Java)file reading (reference documentation)network requests (documentation references to cloud.google.com domains)

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

gke cluster setupchoose gke skillgke routingkubernetes engine basicsmcp vs gcloud preferencegke quick startkubernetes cluster discovery

Risk Signals

INFO

Shell eval/exec of dynamic content detected in cli-reference.md

references/cli-reference.md | exec pattern

Referenced Domains

External domains referenced in skill content, detected by static analysis.

cloud.google.comdocs.cloud.google.comgithub.comregistry.terraform.iowww.apache.org

Use Cases

  • Determining which GKE skill to load for a specific workload (networking, security, scaling, etc.)
  • Understanding GKE cluster modes, architecture, and networking model
  • Learning about tool preferences (MCP vs gcloud vs kubectl) and when to use each
  • Setting up a basic Autopilot cluster with quick-start commands
  • Troubleshooting GKE operations using CLI, MCP tools, and error handling guides
  • Discovering available Kubernetes client libraries and usage patterns
  • Planning GKE infrastructure using Terraform providers

Quality Notes

  • Strong structure with clear routing table and scenario-based decision matrix
  • Comprehensive reference documentation covering multiple integration patterns (MCP, CLI, IaC, client libraries)
  • Excellent tool preference documentation with explicit fallback chains and user override guidance
  • Good error handling table with specific causes and remediation steps
  • Clear boundary statement ('Do not use for specialized tasks') reduces scope confusion
  • Terraform examples are complete and runnable; Python, Go, JavaScript, Java examples are concise and functional
  • Quick-start commands are minimal but sufficient for initial cluster creation
  • Missing explicit examples of when NOT to use the skill or advanced use case limitations
Model: claude-haiku-4-5-20251001Analyzed: Jun 28, 2026

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Version History

  1. v2.0

    Contract changed: description

    ✦ AIRepurposed from comprehensive GKE guide to discovery and routing hub for specialized GKE skills; removed 21 detailed references and example assets.

    triggeringlicense2026-06-28

    Latest
  2. v1.0

    2026-05-02

    Initial version

Use google/gke-basics in your dev environment

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