gcp-cloud
Google Cloud Platform infrastructure patterns and best practices. Use when designing or implementing GCP solutions including Compute Engine, Cloud Functions, Cloud Storage, and BigQuery.
Best use case
gcp-cloud is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Google Cloud Platform infrastructure patterns and best practices. Use when designing or implementing GCP solutions including Compute Engine, Cloud Functions, Cloud Storage, and BigQuery.
Teams using gcp-cloud should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/gcp-cloud/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How gcp-cloud Compares
| Feature / Agent | gcp-cloud | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Google Cloud Platform infrastructure patterns and best practices. Use when designing or implementing GCP solutions including Compute Engine, Cloud Functions, Cloud Storage, and BigQuery.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GCP Cloud Skill
This skill provides GCP architecture patterns and best practices.
## Core Services
| Service | Use Case |
|---------|----------|
| Compute Engine | Virtual machines |
| Cloud Functions | Serverless functions |
| Cloud Run | Containers serverless |
| Cloud Storage | Object storage |
| Cloud SQL | Managed databases |
| BigQuery | Data warehouse |
| GKE | Kubernetes |
## Terraform Patterns
```hcl
# GKE cluster
resource "google_container_cluster" "primary" {
name = "my-cluster"
location = "us-central1"
remove_default_node_pool = true
initial_node_count = 1
workload_identity_config {
workload_pool = "${var.project_id}.svc.id.goog"
}
}
```
## Security Best Practices
- Use Workload Identity (not service account keys)
- Enable VPC Service Controls
- Use Cloud IAM for access management
- Enable Cloud Audit Logs
- Use Customer-Managed Encryption Keys
- Enable Binary Authorization for GKE
## BigQuery Patterns
```sql
-- Partitioned table for cost optimization
CREATE TABLE mydataset.events
PARTITION BY DATE(event_time)
CLUSTER BY user_id
AS SELECT * FROM staging.events;
```
## Cost Optimization
- Use Committed Use Discounts
- Use Preemptible VMs for batch
- Enable autoscaling
- Use BigQuery slot reservations
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