k8s-simple-deploy
Assists with deploying simple apps to Kubernetes consisting of a deployment and a service.
Best use case
k8s-simple-deploy is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Assists with deploying simple apps to Kubernetes consisting of a deployment and a service.
Teams using k8s-simple-deploy should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/k8s-simple-deploy/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How k8s-simple-deploy Compares
| Feature / Agent | k8s-simple-deploy | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Assists with deploying simple apps to Kubernetes consisting of a deployment and a service.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Kubernetes simple deploy skill Use this skill when users want to deploy a basic app on the Kubernetes cluster. ## Instructions - Expect the user to provide the name for an app they wish to deploy, along with a docker image reference. Optionally they may supply number of replicas and port number, but these are not required, and have defaults. - Call the script `scripts/deploy-app.py` passing the supplied name, image, and optional parameters (# of replicas and port number) if supplied, in that order. - The script generates a correct two-resource manifest (Deployment + Service) and writes it to the file `temp-manifest.yaml`. You, the **agent**, are expected to apply the generated manifest `temp-manifest.yaml` against the current Kubernetes context. ## Example ```text User: Deploy an app called "nginx" using image "docker/nginx" with 2 replicas on port 8080. Agent: Invokes `scripts/deploy-app.py nginx docker/nginx 2 8080` ``` The "skill" creates a manifest named `temp-manifest.yaml` consisting of a Deployment + Service in one shot. The Agent in turn applies the generated temp-manifest.yaml to the cluster.
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