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K8s Manifest Generator

CommunityPopular
wshobson
k8s-manifest-generator

Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

Overview

Publisherwshobson
Repositoryagents
Skill namek8s-manifest-generator
Stars
40.1K
Forks
4.3K
Bundled files
6
LicenseMIT
Links
  • 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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by wshobson on GitHub. Read the source before you install it.

Installation

Install the K8s Manifest Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/wshobson/agents/tree/main/plugins/kubernetes-operations/skills/k8s-manifest-generator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/wshobson/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/plugins/kubernetes-operations/skills/k8s-manifest-generator .claude/skills/k8s-manifest-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable K8s Manifest Generator 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 K8s Manifest Generator 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 K8s Manifest Generator 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.

Kubernetes Manifest Generator

Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims.

Purpose

This skill provides comprehensive guidance for generating well-structured, secure, and production-ready Kubernetes manifests following cloud-native best practices and Kubernetes conventions.

When to Use This Skill

Use this skill when you need to:

  • Create new Kubernetes Deployment manifests
  • Define Service resources for network connectivity
  • Generate ConfigMap and Secret resources for configuration management
  • Create PersistentVolumeClaim manifests for stateful workloads
  • Follow Kubernetes best practices and naming conventions
  • Implement resource limits, health checks, and security contexts
  • Design manifests for multi-environment deployments

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Best Practices Summary

  1. Always set resource requests and limits - Prevents resource starvation
  2. Implement health checks - Ensures Kubernetes can manage your application
  3. Use specific image tags - Avoid unpredictable deployments
  4. Apply security contexts - Run as non-root, drop capabilities
  5. Use ConfigMaps and Secrets - Separate config from code
  6. Label everything - Enables filtering and organization
  7. Follow naming conventions - Use standard Kubernetes labels
  8. Validate before applying - Use dry-run and validation tools
  9. Version your manifests - Keep in Git with version control
  10. Document with annotations - Add context for other developers

Troubleshooting

Pods not starting:

  • Check image pull errors: kubectl describe pod <pod-name>
  • Verify resource availability: kubectl get nodes
  • Check events: kubectl get events --sort-by='.lastTimestamp'

Service not accessible:

  • Verify selector matches pod labels: kubectl get endpoints <service-name>
  • Check service type and port configuration
  • Test from within cluster: kubectl run debug --rm -it --image=busybox -- sh

ConfigMap/Secret not loading:

  • Verify names match in Deployment
  • Check namespace
  • Ensure resources exist: kubectl get configmap,secret

Next Steps

After creating manifests:

  1. Store in Git repository
  2. Set up CI/CD pipeline for deployment
  3. Consider using Helm or Kustomize for templating
  4. Implement GitOps with ArgoCD or Flux
  5. Add monitoring and observability

Related Skills

  • helm-chart-scaffolding - For templating and packaging
  • gitops-workflow - For automated deployments
  • k8s-security-policies - For advanced security configurations

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the K8s Manifest Generator AI skill do?

Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

Why use K8s Manifest Generator on TypingMind?

Because you install it once and use it with any model. K8s Manifest Generator 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 K8s Manifest Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wshobson/agents/tree/main/plugins/kubernetes-operations/skills/k8s-manifest-generator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use K8s Manifest Generator?

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 K8s Manifest Generator?

As many as you like. As long as a model supports skills, you can use K8s Manifest Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the K8s Manifest Generator AI skill free?

Yes. It is published on GitHub by wshobson under the MIT 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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