gke-app-onboarding

gke-app-onboarding is a skill for Claude Code, Codex from gke-labs/kube-agents. It costs 70 tokens per session (1,213 once invoked), scanned A, original, Apache-2.0.

A workflow for preparing an application to run on Google Kubernetes Engine (GKE), Google's managed service for running applications in containers. It covers assessing the app, creating a container image, and deploying it with Kubernetes configuration.

In plain words
What is it for?
Use it to containerize an application, create deployment manifests, apply them to GKE, inspect resources and logs, and check rollout status.
Why use it?
It brings together the checks needed when an application is moving to GKE for the first time, including dependencies, configuration, storage, networking, and health checks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to containerize an application, create deployment manifests, apply them to GKE, inspect resources and logs, and check rollout status.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gke-labs/kube-agents/gke-app-onboarding
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.

Any agent
npx skills add gke-labs/kube-agents --skill gke-app-onboarding
Clone the repo
git clone --depth 1 https://github.com/gke-labs/kube-agents

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for gke-app-onboarding

README.md
[![agentmods](https://agentmods.dev/badge/skills/gke-labs/kube-agents/gke-app-onboarding/github.svg)](https://agentmods.dev/skills/gke-labs/kube-agents/gke-app-onboarding)
Your own site
<a href="https://agentmods.dev/skills/gke-labs/kube-agents/gke-app-onboarding"><img src="https://agentmods.dev/badge/skills/gke-labs/kube-agents/gke-app-onboarding/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gke-app-onboarding

Your own site · 80×15
<a href="https://agentmods.dev/skills/gke-labs/kube-agents/gke-app-onboarding"><img src="https://agentmods.dev/badge/skills/gke-labs/kube-agents/gke-app-onboarding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,213 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.01213
Opus 5 $0.00035 $0.00607
Sonnet 5 $0.00014 $0.00243
Haiku 4.5 $0.00007 $0.00121

Measured 12d ago against content hash d9133859907d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

gke-app-onboarding 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (assets/index.js), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

agents/platform/skills/gke-app-onboarding/SKILL.md · 186 lines

How it starts

The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GKE App Onboarding

This reference provides workflows for containerizing and deploying applications to GKE for the first time.

MCP Tools: apply_k8s_manifest, get_k8s_resource, get_k8s_rollout_status, get_k8s_logs, describe_k8s_resource

Workflow

1. App Assessment

Before containerizing, assess the application:

  • Language & Framework: Identify the tech stack
  • Dependencies: List required libraries and external services
  • Configuration: How is the app configured? (env vars, config files, secrets)
  • Statefulness: Does it need persistent storage? (databases, file storage)
  • Networking: Port mapping and protocol (HTTP, gRPC, TCP)
  • Health endpoints: Does the app expose health check endpoints?

2. Containerization

Create a container image:

Dockerfile (recommended for most apps):

# Multi-stage build for smaller, more secure images
FROM golang:1.22 AS builder
WORKDIR /app
COPY . .
RUN CGO_ENABLED=0 go build -o server .

FROM gcr.io/distroless/static:nonroot
COPY --from=builder /app/server /server
USER nonroot:nonroot
EXPOSE 8080
ENTRYPOINT ["/server"]

Best practices:

  • Use multi-stage builds to keep production images small
  • Use distroless or minimal base images to reduce attack surface
  • Run as non-root user
  • Log to stdout and stderr for Cloud Logging collection

For applications where writing a Dockerfile is not preferred, you can use Cloud Native Buildpacks to automatically detect the language and build a container image:

pack build <image> --builder gcr.io/buildpacks/builder:latest

3. Image Management

Build and store the container image:

# Configure Docker for Artifact Registry
gcloud auth configure-docker <REGION>-docker.pkg.dev --quiet

# Build and push
docker build -t <REGION>-docker.pkg.dev/<PROJECT>/<REPO>/<IMAGE>:<TAG> .
docker push <REGION>-docker.pkg.dev/<PROJECT>/<REPO>/<IMAGE>:<TAG>

Read the full file on GitHub · 186 lines

Files

What ships with it

4 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.

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.

  1. 12d ago First seen · 186 lines · 70 tokens per session scan A d9133859907d

Subscribe to this mod's changes

gke-app-onboarding is a skill published in the GitHub repository gke-labs/kube-agents (54 stars, last pushed today), licensed Apache-2.0. It adds 70 tokens to every session and 1,213 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 2026-08-30.

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