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Kubernetes_Hpa

Checked
davidcastagnetoa·vlatest·cloud

Automatically scales Kubernetes deployments based on resource utilization using Horizontal Pod Autoscaling (HPA).

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 davidcastagnetoa/skills --skill kubernetes_hpa -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

davidcastagnetoa

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 davidcastagnetoa/skills at bd906f22af.

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

Commit
bd906f22af
Manifest
skills/kubernetes_hpa/SKILL.md
Scanned
1 file, 214 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 allows AI agents to manage Kubernetes Horizontal Pod Autoscalers (HPAs). It can automatically scale the number of pods in a deployment, replication controller, or replica set based on observed CPU utilization or other metrics. This ensures applications have sufficient resources while optimizing resource usage and cost.

When to use it

  • Responding to traffic spikes: Automatically increase pod count during periods of high demand.
  • Optimizing cloud costs: Reduce the number of pods when load is low, minimizing infrastructure expenses.
  • Maintaining application performance: Ensure consistent response times even under varying workloads by dynamically adjusting resources.
  • Automating scaling decisions: Eliminate manual intervention in resource allocation and scaling processes.

Key capabilities

  • Create HPAs based on CPU utilization.
  • Scale deployments, replication controllers, or replica sets.
  • Automatically adjust the number of pods.

Example prompts

  • "Create an HPA for my 'web-app' deployment that targets 70% CPU utilization."
  • "Scale down the number of pods in my 'database' replica set when CPU usage is consistently low."
  • “What’s the current target CPU utilization for my ‘api’ deployment?”

Tips & gotchas

  • Requires access to a Kubernetes cluster and appropriate permissions.
  • Ensure metrics server is properly configured within your Kubernetes cluster for accurate resource monitoring.