This repository contains a growing collection of Agent Skills for Google Cloud Storage. These skills deliver vetted GCS expertise directly into your coding agent, letting you use natural language prompts in your preferred CLI or IDE to work with your storage resources — from everyday bucket and object management to security assessments and infrastructure code generation.
Note
This repository is under active development. More skills will be added over time.
Important
We Want Your Feedback! Please share your thoughts with us by opening an issue on GitHub. Your input is invaluable and helps us improve the project for everyone.
- Installation
- Available Skills
- Prerequisites
- Authentication
- Example Use Cases
- Google Cloud Storage Basics Skill
- GCS Security Assessment Skill
- Security Reminder: Agent Environment Hardening
- Support
- Contributing
- License
npx skills add gemini-cli-extensions/google-cloud-storageFrom the npx install command, you can select the specific skills from this
repo to install. The skills work with any compatible coding agent, including
Gemini CLI, Claude Code, Codex, and Antigravity CLI.
- Google Cloud Storage Basics — Everyday GCS expertise: create and configure buckets; upload, download, and transfer data; control access; manage storage classes, lifecycle, and data protection; mount buckets with gcsfuse; and work through the gcloud CLI, JSON/XML APIs, client libraries, Terraform, or Cloud Storage MCP servers.
- GCS Security Assessment — Assesses the security posture of Google Cloud Storage projects and buckets, identifying toxic combinations of vulnerabilities and checking SAIF compliance.
Ensure you have the following:
- A Google Cloud project with the resources you want to work with.
- Google Cloud SDK (gcloud CLI): Install and initialize the gcloud CLI and ensure Application Default Credentials (ADC) are configured.
- A compatible coding agent, such as Gemini CLI, Claude Code, Codex, or Antigravity CLI.
Before using the skills, authenticate with Google Cloud so your agent can read your storage resources and run any changes you approve. It is recommended to run both of the following commands:
gcloud auth login
gcloud auth application-default logingcloud auth application-default loginis required: skill scripts use Application Default Credentials (ADC) to generate access tokens for GCP API calls.gcloud auth loginallows the agent (or you) to run standardgcloudcommands to explore configurations or dig deeper into specific resources beyond what the skill scripts cover.
The skills cover the full storage lifecycle — provisioning, data movement, access control, protection and compliance, cost, security, and automation. Interact with Google Cloud Storage using natural language, right from your coding agent:
- Quick start: "Create a new GCS bucket named 'audio-video-assets' in the 'my-gcp-project' project"
- Sensitive data: "Create a secure GCS bucket to store PII and other sensitive data. Make sure the data is protected against exfiltration and unauthorized public exposure"
- Media serving: "I am building a high-performance media streaming service that delivers millions of high-definition images and videos to a global audience. Set up a Cloud Storage bucket as the origin, paired with a global Content Delivery Network (CDN), to minimize latency and ensure optimal streaming performance at scale"
- AI/ML workloads: "I have a large-scale model training and checkpointing use case. Help me set up GCS to optimize performance"
- Cloud migration: "Migrate the data in my S3 bucket 'legacy-exports' into a new GCS bucket"
- Disaster recovery: "Set up continuous replication of bucket 'ops-bucket' to bucket 'vault-bucket-isolated', and ensure all the existing historical data is copied as well"
- Zero-downtime moves: "Relocate my 'analytics-archive' bucket from us-east1 to us-central1 without downtime"
- Temporary sharing: "How can I temporarily give one of my users access to upload a large video to my bucket?"
- Troubleshooting: "I got a 403 Forbidden error. Help me diagnose and fix it"
- Recovery: "I accidentally deleted objects from the 'prod-reports' bucket. Can I get them back?"
- Immutability: "Configure my 'audit-logs' bucket so objects cannot be deleted or modified for 7 years"
- Cost analysis: "Analyze my buckets and recommend storage classes and lifecycle rules to reduce storage costs"
- Usage insight: "Find my largest and least-accessed datasets across all buckets in the project"
- Targeted assessment: "Assess the security posture of buckets [BUCKET_1], [BUCKET_2] in project [PROJECT_ID]"
- Project-wide assessment: "Run a security assessment of project [PROJECT_ID] and show me the exact commands to remediate any toxic combinations you find"
- Terraform: "Generate a Terraform configuration to provision a GCS bucket in us-central1 for application logs. Make sure public access is prevented and Uniform Bucket-Level Access is enabled, and add a lifecycle rule to transition logs to Nearline storage after 30 days and delete them after 365 days"
- Client libraries: "Generate Java code to upload a local directory to my 'app-backups' bucket in parallel using the Cloud Storage client library"
- File-system access: "Help me mount the 'ml-datasets' bucket as a local file system with gcsfuse, with mount options tuned for high-throughput model training"
- Event notifications: "Send a Pub/Sub notification whenever new objects land in my 'ingest' bucket so my pipeline can process them"
- Agentic workflows: "Scan the 'retail-raw-products' bucket for assets related to 'ProductX', draft a promotional social media campaign listing, and write the draft output file to bucket 'retail-campaigns'"
The Google Cloud Storage Basics skill covers day-to-day work with GCS: bucket
creation and configuration, object and folder management, uploads, downloads,
and large-scale transfers, access control (IAM, ACLs, signed URLs, public access
prevention), storage classes and lifecycle management, data protection
(versioning, encryption, retention, soft delete), gcsfuse mounts, and
performance tuning. It guides your agent across the gcloud CLI, JSON and XML
APIs, client libraries, Terraform, and Cloud Storage MCP servers, backed by the
curated reference docs in
skills/google-cloud-storage-basics/.
No permissions are required beyond the prerequisites and whatever IAM access your identity already has to the buckets you work with.
The GCS Security Assessment skill is grounded in Google's Secure AI Framework (SAIF). Rather than emitting isolated static alerts, it correlates real telemetry signals gathered from your project to surface toxic combinations of vulnerabilities—scenarios where individually low-risk configurations combine to create a critical exposure—and provides actionable, verified remediation.
Tip
For the best analysis, we highly recommend being a Storage Intelligence customer. When Storage Intelligence is enabled, the skill can query your Storage Insights datasets to perform deep, bucket-level and object-level assessments. Without it, the skill falls back to a project-level assessment only.
The only hard requirement is working Application Default Credentials (see
Authentication). There is no required IAM permission—any
authenticated identity can run the skill, though signals it cannot read are
reported as UNKNOWN.
For a complete assessment, grant the recommended read-only roles covering
Storage Insights telemetry (bucket/object analysis) and project-level posture
(IAM and audit config, org policies, VPC Service Controls, and Model Armor). See
PERMISSIONS.md for the full permission tables and a
ready-to-apply custom IAM role
(gcs-security-assessment-role.yaml).
Interact with your coding agent using natural language:
- Assess an entire project:
Assess the security posture of project [PROJECT_ID] - Assess a specific subset of buckets:
Assess the security posture of buckets [BUCKET_1], [BUCKET_2] in project [PROJECT_ID] - Follow-up investigation: After an assessment, ask the agent to drill
into a finding—for example, "Explain why the
ml-training-databucket is flagged as a toxic combination" or "Show me the exact command to remediate the public access finding."
The agent works through a fixed, auditable sequence of phases—discovering scope and gathering telemetry, classifying buckets, evaluating baseline security, analyzing toxic combinations, and producing a formatted report—so you can trace every finding back to a signal it actually collected.
Your agent can execute tools and commands on your behalf. Protect your Google Cloud resources by enforcing The Principle of Least Privilege across all CLIs, MCP servers and other resources available to your agents.
- Service Accounts: Use service accounts instead of end user credentials to access Google Cloud resources.
- Limited Permissions: Assign roles with limited permissions to the service account that you're using for authentication.
- Principal Access Boundaries: Prevent unwanted cross-org agent access by using Principal Access Boundary policies to scope your agent to projects you intend it to access.
- Include a condition in the policy binding to ensure that the policy only applies to the service accounts that you intend to restrict.
You can read more here on how to mitigate prompt injection attacks with Google Cloud MCP.
If you need help or encounter issues with these skills, search for existing issues or open a new one in the GitHub Issue Tracker.
We welcome contributions to improve these skills. You can help by:
- Reporting bugs or inaccuracies in the skill files.
- Suggesting new skills to add to this repository by filing a feature request.
You are free to copy, modify, and distribute these skills under the terms of the
Apache 2.0 license. See the LICENSE file for details.