Gcp
Google Cloud Platform with Cloud Run, GKE, and BigQuery. Use for GCP infrastructure.From its SKILL.md
npx -y skills add G1Joshi/Agent-Skills --skill gcpAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 12 stars12 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
1.4 KB, 312 tokens by cl100k_base, as published. Nobody here has run it
Google Cloud Platform (GCP)
GCP is known for its data analytics (BigQuery) and being the home of Kubernetes. 2025 highlights Vertex AI for rapid model deployment and Cloud Run for serverless everywhere.
When to Use
- Big Data: BigQuery is arguably the best data warehouse for speed and ease of use.
- Kubernetes: GKE (Google Kubernetes Engine) often leads in features and stability (Autopilot).
- AI: TPU access and Vertex AI for training large models.
Core Concepts
Projects
The primary unit of isolation. Resources belong to a Project. Projects belong to Folders/Organization.
Global VPC
Unlike AWS/Azure, GCP VPCs are global. Subnets are regional. A single VPC can span the world.
IAM
Permissions are granted to Members (Users/Service Accounts) on Resources via Roles.
Best Practices (2025)
Do:
- Use Cloud Run: The default computed choice for stateless containers. Scales to zero, fast startup.
- Use Workload Identity: Let GKE workloads impersonate Service Accounts securely.
- Shared VPC: For orgs, use a Shared VPC in a Host Project to centralize networking.
Don't:
- Don't use
ownerrole: It's too broad. Use precise roles (storage.objectViewer).
References
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.