Kubernetes Orchestration
CheckedAutomates Kubernetes cluster deployment, scaling, and management using spjoshis's expertise for optimized cloud infrastructure.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add spjoshis/claude-code-plugins --skill kubernetes-orchestration -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
spjoshis
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.
Automated safety checks
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 spjoshis/claude-code-plugins at ddcf16ef7b.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- ddcf16ef7b
- Scanned
- 1 file, 114 lines
About this skill
What it does
This skill allows AI agents to interact with and manage Kubernetes clusters. It can deploy applications, scale resources based on demand, and troubleshoot common issues within a Kubernetes environment. The agent can execute commands against your cluster using kubectl and interpret the results.
When to use it
- Automated deployments: Deploy new versions of an application to your Kubernetes cluster without manual intervention.
- Resource scaling: Automatically increase or decrease the number of pods based on real-time traffic patterns.
- Troubleshooting: Diagnose and resolve issues within a Kubernetes environment, such as pod failures or resource constraints.
- Cluster management: Perform routine maintenance tasks like rolling updates and node upgrades.
Key capabilities
kubectlcommand execution- Resource deployment (pods, services, deployments)
- Scaling of resources
- Troubleshooting assistance
Example prompts
- "Deploy the latest version of my application to the 'staging' Kubernetes cluster."
- "Scale the number of pods for service 'my-app' based on CPU utilization."
- "What is the status of pod 'nginx-deployment-789f456b7-abcde'?"
Tips & gotchas
- This skill requires appropriate
kubectlconfiguration and access to your Kubernetes cluster. Ensure the AI agent has the necessary credentials and permissions.