What problem does it solve? Working with Google Cloud Storage involves many surfaces — the gcloud storage CLI, JSON and XML APIs, client libraries, Terraform, and MCP servers — each with its own commands, flags, and pitfalls. This Skill gives an AI agent the correct, current commands and decision guidance for storing, retrieving, securing, and managing objects in GCS buckets without guesswork. ## Core Features & Use Cases - Bucket and Object Operations: Create buckets, upload, download, copy, and delete objects using gcloud storage or the JSON API, with guidance on locations, storage classes, and lifecycle rules. - Security and Data Protection: Configure IAM roles, uniform bucket-level access, public access prevention, signed URLs, encryption (CMEK/CSEK), versioning, soft delete, retention policies, and Bucket Lock. - Transfers and Performance: Choose between gcloud storage cp/rsync, parallel composite uploads, and Storage Transfer Service for S3/Azure migrations, plus Rapid Bucket, Rapid Cache, hierarchical namespace, and gcsfuse mounts for AI/ML workloads. - Use Case: Migrate an on-premises dataset to GCS, enable Autoclass for cost optimization, set a retention policy for compliance, and mount the bucket on a GKE cluster for ML training — all with correct commands. ## Quick Start Ask the agent to create a Cloud Storage bucket in a specific region and upload a local file to it using the gcloud storage CLI.