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google/google-cloud-storage-bucket-architect

google

google-cloud-storage-bucket-architect

Creates Cloud Storage (Google Cloud Storage, or 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.

v1.0LATEST
NewUpdated Sep 4, 2026

Google Cloud Storage Bucket Architect

You are a Use-Case Driven Google Cloud Storage Bucket Architect agent. 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 bucket commands, including 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, 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-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 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:

  1. 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.

  2. 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. 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.

  3. 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.

References

Phases

Bucket Use Cases

Provisioning & Output Formats

SDK Language-Specific Guides

  • C++ SDK Guide: Code examples and patterns for the Google 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 Google Cloud Storage Python client library.
Files20
20 files · 239.5 KB

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Overall Score

87/100

Grade

A

Excellent

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

88

Quality

89

Clarity

87

Completeness

84

Summary

A comprehensive, use-case-driven Cloud Storage bucket architecture skill that guides agents through a structured three-phase workflow: project-level security checks, workload-specific bucket design, and multi-format output generation (gcloud, REST, Terraform, SDK). The skill includes 19 reference files covering 8 distinct use cases, provisioning methods, and language-specific implementations, with built-in guardrails against unauthorized execution.

Detected Capabilities

gcloud command generationREST API payload constructionTerraform HCL generationSDK code snippet generation (C++, Go, Java, Python)project-level security assessment via gcloud queriesbucket configuration planning and validationIAM policy recommendationsencryption and CSEK enforcement configuration

Trigger Keywords

Phrases that agents use to match this skill to user intent.

design gcs bucketcloud storage architecturebucket security configurationcreate cloud storage bucketgcs compliance setupstorage for ai trainingbackup bucket replicationwebsite hosting on storage

Risk Signals

INFO

Agent is instructed to execute gcloud org-policies describe and resource-manager liens list commands during Phase 1 project checks

references/phase_project_checks.md:Step 1
INFO

Agent must execute gcloud commands only after explicit user confirmation, with clear prohibition against auto-execution

SKILL.md: CAUTION block, references/phase_output.md: Step 3
INFO

Skill references handling of destructive operations (retention policy locking, hard deletes) with explicit irreversibility warnings and confirmation requirements

references/archiving_compliance.md, references/phase_draft_plan.md (Retention Policy Decisions section)
INFO

Attribution tagging is required for all gcloud, REST, and other monitored operations to enable usage tracking

SKILL.md: Attribution section

Referenced Domains

External domains referenced in skill content, detected by static analysis.

cloud.google.comexample.appspot.comexample.commy-website.appspot.compkg.go.devregistry.terraform.iostorage.googleapis.comwww.apache.org

Use Cases

  • design secure GCS bucket for sensitive PII/HIPAA data
  • provision multi-regional media hosting CDN origin
  • set up backup and disaster recovery storage
  • configure direct UGC ingestion with signed URLs
  • deploy static website hosting on Cloud Storage
  • create long-term archive with compliance locking
  • build AI/ML training and checkpoint storage
  • configure high-volume log ingestion and SIEM integration

Quality Notes

  • Excellent structural clarity: Three-phase workflow is explicitly defined with clear handoff points and no ambiguity about phase ordering
  • Comprehensive reference documentation: 19 supporting files cover all major GCS use cases, provisioning formats, SDK languages, and security patterns
  • Strong guardrails: Explicit cautions against auto-execution, irreversibility warnings for Bucket Lock, and confirmation requirements are well-documented
  • Secure-by-default philosophy: UBLA, PAP, soft delete, and CSEK restriction are mandated as defaults unless explicitly overridden by user with documented risk acknowledgment
  • Language-specific SDK examples: All four major SDK languages (C++, Go, Java, Python) have worked examples with version requirements clearly stated
  • Feature support matrix: Clear documentation of which features are exposed/unexposed in each SDK, with fallback guidance for unsupported features
  • Well-structured phase handling: Each phase (checks, plan, output) has defined inputs, outputs, error handling, and decision trees
  • Edge case coverage: Zonal buckets, IP filtering constraints, dual-region considerations, and hierarchical namespace incompatibilities are all explicitly addressed
  • Attribution and monitoring compliance: Skill includes metrics environment variable tagging for gcloud and User-Agent headers for REST to enable usage tracking
Model: claude-haiku-4-5-20251001Analyzed: Sep 4, 2026

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