- name
- gcp-project-bootstrap
- description
- Create and bootstrap Google Cloud projects for new workloads. Use when the user wants to create a new Google Cloud project, choose a project ID and naming convention, decide billing and region setup, enable required Google APIs, prepare service accounts, or initialize a project for Cloud Run, Vertex AI, BigQuery, Cloud Storage, or Firebase. Also use when auditing whether a planned GCP project setup is complete before deployment.
GCP Project Bootstrap
Create new Google Cloud projects in a deliberate, least-privilege way.
Workflow
- Clarify the workload first.
- Cloud Run app - Vertex AI / Gemini / ML workload - BigQuery / analytics - Cloud Storage / file hosting - Firebase app - sandbox / experiment / tutorial
- Collect required inputs before proposing commands.
- project display name - desired project_id - org/folder placement if applicable - billing account availability - primary region or residency requirement - services that must work on day one - whether CI/CD or runtime service accounts are needed
- Read
references/project-creation-checklist.mdand follow it as the default sequence.
- If billing, API enablement, or service selection is part of the task, read
references/billing-and-apis.md.
- If command examples are needed, read
references/common-gcloud-commands.md.
Operating rules
- Do not assume billing is already linked.
- Do not recommend broad roles like
roles/ownerunless the user explicitly asks and understands the risk. - Prefer least privilege and workload-specific service accounts.
- Call out when a step requires console-only actions, elevated org permissions, or a human with billing admin access.
- If the user has not chosen a region, explain the tradeoff briefly instead of picking randomly.
- If the project is for production, recommend enabling audit-friendly naming and separating runtime/service identities early.
Output expectations
When helping the user, produce:
- a short summary of the intended project purpose
- the exact inputs still missing
- a safe creation sequence
- API list grouped by workload
- IAM/service-account recommendations only if relevant
Common workload branches
Cloud Run
Focus on:
- Artifact Registry
- Cloud Build
- Cloud Run Admin API
- runtime service account
- region choice close to users/data
Vertex AI
Focus on:
- billing must be active
- Vertex AI API
- region support for the intended model/service
- storage buckets for datasets/artifacts if needed
- service account separation for notebooks/jobs/apps
BigQuery
Focus on:
- dataset region planning
- billing confirmation
- BigQuery API
- least-privilege access for analysts vs pipelines
Firebase
Focus on:
- whether this is primarily a Firebase project with GCP underneath
- required console setup beyond raw
gcloud - auth/hosting/firestore specific downstream decisions