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Kubernetes Workload Design

Checked
kentoshimizu·vlatest·cloud·Apache-2.0

Helps with Kubernetes, design as part of deploying and managing cloud infrastructure workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add kentoshimizu/sw-agent-skills --skill kubernetes-workload-design -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

kentoshimizu

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned kentoshimizu/sw-agent-skills at 5b7bafb626.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
5b7bafb626
Manifest
skills/kubernetes-workload-design/SKILL.md
Scanned
4 files, 91 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill assists in designing Kubernetes workloads, focusing on resource allocation and configuration. It can help determine appropriate CPU and memory requests and limits for containers within pods, ensuring efficient resource utilization and preventing resource contention. The skill aims to optimize workload performance and stability within a Kubernetes cluster.

When to use it

  • You're deploying a new application to Kubernetes and need guidance on setting initial resource requests and limits.
  • Existing workloads are experiencing performance issues or instability due to resource constraints.
  • You want to proactively right-size your Kubernetes deployments for cost optimization.
  • You’re troubleshooting “out of memory” (OOM) errors in your pods.

Key capabilities

  • Resource request and limit calculation
  • Pod configuration assistance
  • Workload optimization recommendations
  • Troubleshooting OOM errors

Example prompts

  • "Suggest resource requests and limits for a Python web server pod."
  • "How can I optimize the memory usage of my Kubernetes deployment?"
  • "My pods are getting OOM killed, what should I check?"

Tips & gotchas

The skill's effectiveness depends on accurate information about the workload’s resource consumption. Providing details about expected traffic patterns and application behavior will improve the quality of recommendations.