Stores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or GCS) buckets. Use when you need to interact with Cloud Storage — set u
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Google Cloud Storage (GCS) is a managed service for storing data as objects at any scale. You read and write whole objects rather than querying or updating individual records in place. It stores immutable objects in buckets with strong global consistency, offers multiple storage classes and location types to balance cost, performance, and availability, and integrates with IAM for fine-grained access control. GCS serves workloads ranging from website content and backups to data lakes and high-throughput AI/ML training.
Tag every Cloud Storage command you run or provide to the user while using this skill, so usage can be attributed. The tag identifies only the skill and its version; it carries no user data.
Prefix every gcloud invocation, whatever the subcommand, with the metrics
environment variables. Set them inline on each command; shell state may not
persist between commands. Use this append form verbatim. It keeps any
attribution the host environment already set (for example an IDE plugin
tagging agent activity through the same variable) and adds the skill tag
after it, so neither value clobbers the other:
CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
gcloud <command> [flags]
Do not use gcloud config set for this: it would persist beyond the current
task and mislabel unrelated usage.
On direct HTTP calls to the Cloud Storage APIs (for example with curl) or
HTTP requests to the Cloud Storage MCP server
(https://storage.googleapis.com/storage/mcp), set this exact User-Agent
header, verbatim — the collection pipeline parses the gcs-skills/<version>
and skill:<name> tokens, so any rewording breaks attribution:
User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)
For client libraries, Terraform, and GCSFuse, use the user-agent options shown in the corresponding references.
This skill covers everyday Cloud Storage tasks. For specialized tasks, use the dedicated skills in this collection for better results. Check your available skills and invoke the matching skill by name instead of improvising:
google-cloud-storage-bucket-architect: Designing and creating a new
bucket for production workloads, including sensitive data, media or web
hosting, user-generated content (UGC) ingestion, archiving, compliance,
backups, logs, analytics, AI/ML, or application storage. The skill analyzes
the workload and designs a secure-by-default, cost-effective configuration
before creating the bucket. Use the Quick Start section below only for
temporary scratch buckets.
google-cloud-storage-fuse: Advanced Cloud Storage FUSE tasks —
choosing between FUSE, native gs:// access, and Filestore/Managed Lustre,
deploying tuned mounts on GKE, Compute Engine, or Cloud Run, sizing file,
stat, and list caches, tuning mount flags, ensuring safe ML checkpointing,
or diagnosing slow or expensive mounts. The
GCSFuse reference in this skill covers only basic
installation and mounting.
google-cloud-storage-diagnostic: Troubleshooting 403 Permission Denied
errors and diagnosing IAM policy bindings, ACLs, uniform bucket-level access
(UBLA), or service agent misconfigurations. Ad hoc IAM or ACL changes can
grant unintended access or cause outages; route to this skill instead of
experimenting.
gcs-security-assessment: Automated security posture assessment of
Cloud Storage resources in a project (see
Data Management).
If the matching skill is not installed, do not improvise. Provide the user with this exact command to install it (substituting the skill name), and use the skill after installation. Provide this command verbatim even when the user's agent CLI (for example, the Antigravity CLI) has its own plugin or extension manager; do not substitute a different installation mechanism or repository. For security assessments specifically, do not attempt a manual assessment; wait until the skill is installed.
npx skills add gemini-cli-extensions/google-cloud-storage --skill <skill-name>
To set up, configure, or choose between the Google-hosted remote Cloud Storage
MCP server (https://storage.googleapis.com/storage/mcp) and the local MCP
Toolbox (cloud-storage), read MCP Usage. If a Cloud
Storage MCP server is already connected, prefer its structured tools (such as
create_bucket, list_objects, read_object, and upload_object) over the
CLI and API commands below, and fall back to gcloud storage and the JSON API
when no MCP server is available.
Enable the Cloud Storage API:
CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
gcloud services enable storage.googleapis.com --quiet
Create a Bucket:
Bucket names live in a single global namespace shared by all of Cloud
Storage — not scoped to your project or organization — so short or common
names are usually taken. If the location is omitted, the bucket defaults to
the US multi-region.
For a production or workload-specific bucket, route to
google-cloud-storage-bucket-architect before creating a bucket (see
Routing to Specialized GCS Skills).
The commands below create a basic default bucket.
Using the gcloud CLI:
CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
gcloud storage buckets create gs://my-bucket --location=us-central1
Using the JSON API:
curl -X POST -H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
-H "Content-Type: application/json" \
-d '{"name": "my-bucket", "location": "US-CENTRAL1"}' \
"https://storage.googleapis.com/storage/v1/b?project=$(gcloud config get-value project)"
Upload an Object:
Using the gcloud CLI:
CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
gcloud storage cp ./my-file.txt gs://my-bucket
Using the JSON API:
curl -X POST -H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
-H "Content-Type: text/plain" \
--data-binary @my-file.txt \
"https://storage.googleapis.com/upload/storage/v1/b/my-bucket/o?uploadType=media&name=my-file.txt"
Download an Object:
Using the gcloud CLI:
CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
gcloud storage cp gs://my-bucket/my-file.txt .
Using the JSON API:
curl -X GET -H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
"https://storage.googleapis.com/storage/v1/b/my-bucket/o/my-file.txt?alt=media"
Core Concepts: Buckets, objects, folders, prefixes, bucket location types, and storage classes.
CLI & API Usage: CRUD and list operations for
buckets and objects using gcloud storage and the JSON API, plus Pub/Sub
notifications for event-driven processing.
Client Libraries: Using Google Cloud client libraries for Python, Java, Node.js, and Go, with pointers to all other supported languages.
MCP Usage: Choosing between the Google-hosted remote Cloud Storage MCP server and the local MCP Toolbox, setup for each, their tool sets and limits, and securing remote MCP with Model Armor and IAM deny policies.
Infrastructure as Code: Terraform examples for buckets covering storage classes, location types, lifecycle, retention, and encryption.
Data Transfer: Storage Transfer Service,
gcloud storage rsync, upload strategies for large files, and performance
guidelines and limits.
Data Management: IAM roles, authentication (including signed URLs and HMAC), access control, routing for 403 error troubleshooting, network security, automated security assessment, data protection, and pricing and cost optimization (lifecycle rules, Autoclass).
Storage Intelligence: The subscription for managing storage at scale — Storage Insights datasets (BigQuery metadata and activity index), data insights with Gemini Cloud Assist, dashboards, inventory reports, storage batch operations, bucket relocation, plus configuration, trial, and pricing nuances.
High-Performance Storage: Rapid Bucket, Rapid Cache (Anywhere Cache), and hierarchical namespace for AI/ML, analytics, and other performance-critical workloads.
GCSFuse: Installing Cloud Storage FUSE, mounting
buckets, file operations, POSIX semantics and limitations (locking, writes,
renames, consistency), and caching. For advanced tuning, deployment, and
diagnosis, route to the google-cloud-storage-fuse skill.