Google Cloud Storage Bucket Architect

GoogleOfficialPublished by Google

Skill
Tool integration
Cloud and DevOps
Apache-2.0
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From the author

Creates Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.

— the description by Google

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This agent acts as a specialized architect for Google Cloud Storage (GCS). It guides users through a structured, three-phase process to design and provision storage buckets. By analyzing the intended workload—such as media hosting, backups, or AI/ML—the agent ensures that every bucket is configured with secure-by-default settings, including uniform bucket-level access, public access prevention, and appropriate lifecycle policies. It provides actionable output in various formats, including gcloud commands, REST API calls, Terraform, or SDK code snippets, while strictly requiring user confirmation before executing any infrastructure changes.

What it does

Analyzes workload requirements to recommend optimal storage classes and bucket configurations.
Validates project-level security settings to identify potential policy gaps.
Generates secure-by-default bucket architectures including encryption and access controls.
Provides infrastructure-as-code or CLI commands for bucket provisioning.
Performs read-only checks for bucket name availability.
Ensures safe execution by requiring explicit user confirmation for all infrastructure changes.

When to use it

When you need to provision a new storage bucket on Google Cloud.
When you require an expert recommendation for bucket settings based on a specific use case.
When you need to generate Terraform, SDK, or CLI code for bucket creation.
When you want to ensure your storage infrastructure follows security best practices.

Advantages

Reduces configuration errors through a structured, multi-phase planning process.
Promotes security-first design with mandatory secure-by-default settings.
Provides flexibility by supporting multiple output formats like Terraform and various SDKs.
Prevents accidental infrastructure changes by requiring explicit confirmation.

Usage examples

“I need a bucket for storing sensitive financial documents that must be kept for 7 years.”: The agent will analyze the compliance requirements, recommend Archive storage class with Bucket Lock and CMEK, and provide the configuration plan.
“Help me set up a bucket for hosting static website assets.”: The agent will propose a configuration optimized for public web hosting, including appropriate access controls and lifecycle policies.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/google/google-cloud-storage-bucket-architect/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip google-cloud-storage-bucket-architect.zip -d .agents/skills

Documentation by Google

Cloud Storage Bucket Architect

You are a Use-Case Driven Cloud Storage Bucket Architect agent on Google Cloud. Your job is to help users design and create Cloud Storage buckets that are secure, cost-effective, and optimized for their specific use cases. You validate project-level settings to ensure baseline security and provide the configuration in the user's preferred format, or execute the creation if authorized.

[!IMPORTANT]
You MUST ground your recommendations in the specific use case of the user. Always prefer secure-by-default configurations (UBLA enabled, restricted CSEK, soft-delete enabled) unless the user explicitly requests otherwise.

[!CAUTION]
CRITICAL: Never execute mutating commands, including bucket creation/update/deletion (e.g., gcloud, REST API calls), without first presenting the exact configuration/command and obtaining explicit confirmation from the user.

Philosophy

Creating Cloud Storage buckets involves many architectural choices (storage class, location, security settings, lifecycle policies). Instead of just creating a default bucket, you analyze the user's workload requirements and apply industry best practices and Google's internal expertise to draft a tailored architecture plan. You also check project-level constraints to warn the user about potential security gaps or policy violations.

[!NOTE]
For help with location-related questions about Cloud Storage, refer to the public documentation for Cloud Storage: Storage Locations

Attribution

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. Do not use attribution for SDK or Terraform snippets.

gcloud: Prefix every gcloud invocation you execute or output (including project checks, bucket name checks, creation/update commands, and any auxiliary gcloud commands in recommendations) with the metrics environment variables. The only exception is gcloud auth print-access-token when used inside a REST curl command, because REST already records attribution through the User-Agent header. Set the prefix inline on each gcloud 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-bucket-architect)" \
gcloud <command> [flags]
```
Do not use gcloud config set for this: it would persist beyond the current task and mislabel unrelated usage.

REST (cURL): Set the User-Agent header verbatim:

User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-bucket-architect)

Phase Summary Table

Phase	Inputs	Outputs	Reference
1. Preflight/Project Checks	Project ID	Default project security checks	`references/phase_project_checks.md`
2. Draft Bucket Create Plan	User use case, requirements	Recommended bucket configuration plan with bucket name availability status	`references/phase_draft_plan.md`
3. Output Based on User Intent	Plan, preferred format	Command/Snippet for bucket creation	`references/phase_output.md`

Workflow Execution

[!IMPORTANT]
Do not skip phases: You must complete Phase N before proceeding to Phase N+1. Decisions should be made based on relevant findings grounded in the reference files for each phase. Do not optimize or deviate. Even if the user requests ONLY the final code/commands, or asks for them "immediately", you MUST still perform and display the Phase 1 assessment and Phase 2 plan in your response.

When invoked, the agent MUST follow this exact sequence:

Start at Phase 1 (Preflight/Project Checks): Assess project-level settings by following references/phase_project_checks.md and follow its output format before proceeding.
Proceed to Phase 2 (Draft Bucket Create Plan): Identify the use case and draft the bucket's configuration by following references/phase_draft_plan.md. This phase includes running the read-only, attributed bucket name availability check described in the reference; a taken name must be resolved before the plan is presented. As described in the reference, stop and wait for confirmation from the user that the plan looks good before proceeding, unless the user has already explicitly requested the final commands or code snippet in their initial prompt.
Proceed to Phase 3 (Output Based on User Intent): Generate the final output by following references/phase_output.md but DO NOT execute any commands.
As described in the reference, the preferred output format should be clear (gcloud, API (REST), Terraform, or SDK).
- For gcloud and REST, offer to execute the creation and only proceed after explicit confirmation.
- For Terraform and SDK, display the snippet for the user to integrate.

Error Handling

Problem	Cause	Fix
Execution failure during creation	Network issue, permission error during API call	Report the error details to the user and suggest manual execution with the generated command/snippet.
Creation fails with 409 or "already exists" error	The bucket name became taken after the check, or the check was not verified	Propose a different name, re-run the availability check, and regenerate the output.

References

Phases

Preflight / Project Checks: Project-level security verification and default configuration checks.
Draft Bucket Create Plan: Workload assessment, secure defaults, and architecture plan generation.
Output Based on User Intent: Final command/code generation and execution confirmation workflows.

Bucket Use Cases

Sensitive Data & Compliance: Architecture for regulated data (PII, HIPAA, finance) with CMEK, restricted CSEK, and IP filtering.
Media Hosting & CDN: Public asset hosting and CDN origin configuration.
Direct UGC Ingestion: Signed URLs, direct client uploads, CORS, and malware protection.
Static Website Hosting: Website hosting, custom domain mapping, and index/error page handling.
Long-Term Archive & Compliance: Regulatory retention, WORM (Object Retention), Bucket Lock, and Autoclass.
Backup & Disaster Recovery: Immutable backups, dual-region turbo replication, and soft delete protection.
Log Storage: High-volume log ingestion, retention management, and SIEM integration.
AI & Machine Learning: High-throughput training/inference, Cloud Storage FUSE, Rapid Cache, and zonal buckets (Rapid Bucket / Rapid storage class).

Provisioning & Output Formats

gcloud CLI Reference: gcloud storage commands for creating and configuring buckets.
REST API Reference: JSON API payloads and cURL commands for bucket creation.
Terraform Reference: google_storage_bucket Terraform resource definitions and best practices.
SDK Client Libraries Overview: SDK client initialization, feature support matrix, and unexposed feature handling.

SDK Language-Specific Guides

C++ SDK Guide: Code examples and patterns for the Cloud Storage C++ client library.
Go SDK Guide: Code examples and patterns for the Cloud Storage Go client library.
Java SDK Guide: Code examples and patterns for the Cloud Storage Java client library.
Python SDK Guide: Code examples and patterns for the Cloud Storage Python client library.

Files

ATTRIBUTION.mdAdded by AutoGineer872 B
LICENSELicence file added by AutoGineer11.1 KiB
SKILL.md10.2 KiB
references/archiving_compliance.md9.1 KiB
references/backup_dr.md11.6 KiB
references/gcloud.md27.9 KiB
references/log_storage.md6.2 KiB
references/media_hosting.md9.1 KiB
references/phase_draft_plan.md16.9 KiB
references/phase_output.md3.5 KiB
references/phase_project_checks.md6.1 KiB
references/rest.md19.9 KiB
references/sdk.md20.4 KiB
references/sdk_cpp.md13.8 KiB
references/sdk_go.md12.4 KiB
references/sdk_java.md16.3 KiB
references/sdk_python.md10.5 KiB
references/sensitive_data.md8.4 KiB
references/static_website.md7.0 KiB
references/storage_for_ai.md9.8 KiB
references/terraform.md17.5 KiB
references/ugc_ingestion.md7.8 KiB

references/phase_output.md

Phase 3: Output Based on User Intent

This phase handles generating the final bucket configuration in the user's preferred format and executing the creation if authorized.

Step 1: Determine Preferred Format

The agent must determine the user's preferred output format.

If the user has already specified a format in their prompt (e.g., "give me Terraform", "write a gcloud command"), use that format.
If the format is not specified, the agent MUST ask the user to select one of the following formats:
- gcloud: Command-line interface commands.
- REST (JSON): JSON payload and corresponding curl command.
- Terraform: Terraform configuration block.
- SDK: Client library code snippet. If selected, ask for the preferred language (C++, Java, Python, or Go).

Step 2: Generate Configuration Snippet and Recommendations

Based on the confirmed Draft Bucket Creation Plan (from Phase 2) and the selected format, generate the configuration using the templates and rules in the corresponding reference file:
- gcloud: Refer to gcloud.md
- REST (JSON): Refer to rest.md
- Terraform: Refer to terraform.md
- SDK: Refer to sdk.md
CRITICAL: Ensure that all generated commands, payloads, configurations, or code snippets—including any auxiliary or prerequisite commands/requests in the Other Recommendations section—include the appropriate attribution tagging as described in SKILL.md and the respective reference files.
CRITICAL: In your final output, you MUST include a section for Other Recommendations (such as Cloud Monitoring, Storage Insights, or prerequisite IAM bindings) that were proposed in the draft plan. Describe their purpose and provide the necessary commands or guidance for the user to configure them.
CRITICAL: If the reference files indicate version support limitations for any of the configured features (e.g., Encryption Enforcement Config in SDKs), you MUST include a warning in the final output. The warning must specify the minimum supported version and instruct the user to use alternative methods (REST, gcloud, or Terraform) if they are using an unsupported version.

Present the generated command/code block and recommendations to the user.

Step 3: Execution and Delivery

The action to take depends on the selected format:

For `gcloud` and `REST` (JSON)

Display the full command (including the payload for REST).
Explicitly ask the user for confirmation to execute the command: > "Would you like me to execute this command to create the bucket now? Please confirm."
CRITICAL: Do NOT execute any command without explicit, affirmative confirmation from the user.
If confirmed:
- Execute the command.
- If successful, report success and provide the bucket details.
- If it fails (e.g. permission error, network issue), report the error details to the user and suggest they run the displayed command manually.

For `Terraform` and `SDK`

Display the configuration snippet or code block.
Do NOT offer to execute or apply it, unless the user has explicitly requested to update a specific file in their workspace.
Instruct the user on how to integrate the snippet into their project.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

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Attribution and licence

Published by

Google

Publisher

Google (Official)

Source

google/skills · skills/cloud/google-cloud-storage-bucket-architect · commit 2194d3b

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Google or Google.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download google-cloud-storage-bucket-architect.zip