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Gcp Cloud Run

Checked
xfstudio·vlatest·cloud

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 xfstudio/skills --skill gcp-cloud-run -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

xfstudio

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 xfstudio/skills at 1bf6044db2.

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

Commit
1bf6044db2
Manifest
gcp-cloud-run/SKILL.md
Scanned
1 file, 264 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 deploy containerized applications directly to Google Cloud Run. It handles tasks like building Docker images, pushing them to Google Container Registry, and configuring Cloud Run services with appropriate settings. The agent can manage deployments, revisions, and scaling based on provided instructions.

When to use it

  • Automating the deployment of a new microservice application to GCP.
  • Creating reproducible environments for testing and development by deploying containerized applications.
  • Scaling existing Cloud Run services up or down based on demand.
  • Updating an existing Cloud Run service with a new version of your code.

Key capabilities

  • Builds Docker images from source code.
  • Pushes Docker images to Google Container Registry (GCR).
  • Deploys containerized applications to Google Cloud Run.
  • Manages Cloud Run services and revisions.

Example prompts

  • "Deploy my application located in /path/to/app to Cloud Run with the service name 'my-service'."
  • "Update the 'my-service' Cloud Run service with the latest Docker image."
  • “Scale ‘my-service’ to 5 instances.”

Tips & gotchas

  • Requires Google Cloud credentials configured for the AI agent.
  • Ensure your application is containerized using a Dockerfile for proper deployment.