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 co…
Install / Use
npx skills add google/skills --skill google-cloud-storage-bucket-architectInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
SecuritySupported Platforms
Our assessment of google-cloud-storage-bucket-architect
google-cloud-storage-bucket-architect scores 90/100 on our quality scale, 261st of 544 Security skills we index (top 48%).
Its SKILL.md is 9.8 KB long, well organised into 11 sections and no code examples: a thorough specification that gives an agent plenty to work with.
With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 2 days ago, so google-cloud-storage-bucket-architect is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
google-cloud-storage-bucket-architect compared with similar skills
All 4 of these similar skills score higher than google-cloud-storage-bucket-architect; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| google-cloud-storage-bucket-architect (this skill)by google | 90 | 20.3k | 2d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
Frequently asked questions
- How do I install google-cloud-storage-bucket-architect?
- Run
npx skills add google/skills --skill google-cloud-storage-bucket-architect. The install tabs above show the steps for each supported agent. - Which AI agents does google-cloud-storage-bucket-architect work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is google-cloud-storage-bucket-architect safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is google-cloud-storage-bucket-architect still maintained?
- The repository was last updated 2 days ago, so google-cloud-storage-bucket-architect is actively maintained.
Skill content
View source on GitHubname: google-cloud-storage-bucket-architect description: >- 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. license: Apache-2.0 metadata: version: "1.0.0" publisher: google tags: "gcs, storage, architect, bucket-creation" category: Storage support_tier: primary
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
gcloudinvocation, 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 setfor this: it would persist beyond the current task and mislabel unrelated usage. -
REST (cURL): Set the
User-Agentheader 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.mdand 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.mdbut DO NOT execute any commands.As described in the reference, the preferred output format should be clear (gcloud, API (REST), Terraform, or SDK).
- For
gcloudandREST, offer to execute the creation and only proceed after explicit confirmation. - For
TerraformandSDK, display the snippet for the user to integrate.
- For
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 storagecommands for creating and configuring buckets. - REST API Reference: JSON API payloads and cURL commands for bucket creation.
- Terraform Reference:
google_storage_bucketTerraform 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 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.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
