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Gcp Gke

Checked
bagelhole·vlatest·cloud·MIT

Provides Google Cloud guidance and assistance for deploying and managing cloud infrastructure.

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 bagelhole/devops-security-agent-skills --skill gcp-gke -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

bagelhole

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 bagelhole/devops-security-agent-skills at 0365f57a07.

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

Commit
0365f57a07
Manifest
infrastructure/cloud-gcp/gcp-gke/SKILL.md
Scanned
1 file, 272 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 interact with and manage Google Kubernetes Engine (GKE) clusters. It enables tasks like listing available GKE clusters, retrieving details about a specific cluster, and potentially deploying applications within those clusters. The skill provides access to core GKE functionalities through the Google Cloud SDK.

When to use it

  • Cluster Inventory: Quickly list all GKE clusters in your Google Cloud project for auditing or reporting purposes.
  • Resource Monitoring: Obtain details about a specific cluster, such as its status, version, and resource utilization.
  • Application Deployment (Potential): While not explicitly stated, the ability to interact with GKE suggests potential for deploying applications to clusters.
  • Troubleshooting: Investigate issues within a GKE cluster by retrieving detailed information about its configuration and state.

Key capabilities

  • Listing GKE Clusters
  • Retrieving Cluster Details
  • Google Cloud SDK Integration

Example prompts

  • "List all my GKE clusters."
  • "What is the status of the 'my-cluster' GKE cluster?"
  • "Show me details about the version running on my GKE cluster named 'production'."

Tips & gotchas

  • Requires appropriate Google Cloud credentials and permissions to access GKE resources. Ensure your AI agent has been configured with a service account or user account that possesses the necessary roles (e.g., roles/container.clusterViewer).