Gcp Expert

This one covers the GCP essentials you'll actually use: Compute Engine, Cloud Functions, BigQuery, Firestore, and Pub/Sub. It includes working Python examples for each service plus gcloud CLI commands for common tasks like spinning up instances and deploying to App Engine. The code samples are solid starting points, though you'll need to adapt them for your project structure and error handling. Best part is the IAM and cost optimization reminders, since that's where most teams get burned. If you're building on GCP and want Claude to help with architecture decisions or debug deployment issues, this gives it the context it needs without drowning in Google's documentation maze.

skills.sh installs: 547
GitHub stars: 44
last updated: Aug 21, 2026

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Install

$ npx -y skills add personamanagmentlayer/pcl --skill gcp-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

Google Cloud Platform Expert

Expert guidance for Google Cloud Platform services and cloud-native architecture.

Core Concepts

Compute Engine, App Engine, Cloud Run
Cloud Functions (serverless)
Cloud Storage
BigQuery (data warehouse)
Firestore (NoSQL database)
Pub/Sub (messaging)
Google Kubernetes Engine (GKE)

gcloud CLI

# Initialize
gcloud init

# Create Compute Engine instance
gcloud compute instances create my-instance \
  --zone=us-central1-a \
  --machine-type=e2-medium \
  --image-family=ubuntu-2004-lts \
  --image-project=ubuntu-os-cloud

# Deploy App Engine
gcloud app deploy

# Create Cloud Storage bucket
gsutil mb gs://my-bucket-name/

# Upload file
gsutil cp myfile.txt gs://my-bucket-name/

Cloud Functions

import functions_framework
from google.cloud import firestore

@functions_framework.http
def hello_http(request):
    request_json = request.get_json(silent=True)
    name = request_json.get('name') if request_json else 'World'

    return f'Hello {name}!'

SKILL.md on GitHub