Execute use when provisioning Vertex AI infrastructure with Terraform. Trigger with phrases like "vertex ai terraform", "deploy gemini terraform", "model garden infrastructure", "vertex ai endpoints terraform", or "vector search terraform". Provisions Model Garden models, Gemini endpoints, vector search indices, ML pipelines, and production AI services with encryption and auto-scaling.
5.8
Rating
0
Installs
DevOps & Infrastructure
Category
A well-structured skill for provisioning Vertex AI infrastructure with Terraform. The description clearly defines trigger phrases and scope (Model Garden, Gemini endpoints, vector search, ML pipelines). The instructions provide a logical 8-step workflow covering configuration, deployment, security, and validation. Structure is clean with references to errors.md and examples.md for details. However, taskKnowledge scores moderately because while it outlines steps, it lacks concrete Terraform code snippets or module patterns in SKILL.md itself (relying entirely on referenced files). Novelty is moderate—while Vertex AI + Terraform integration has complexity, much of this involves standard IaC patterns that experienced developers could construct, though the production guardrails (encryption, auto-scaling, IAM) add value. The skill would benefit from including at least one minimal code example inline to demonstrate the Terraform patterns for Vertex AI resources.
jeremylongshore
Skill Author
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