About

Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/vertex-infra-expert/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill vertex-infra-expert. Copyright stays with the author (MIT).

Vertex Infra Expert

Name: vertex-infra-expert
Author: jeremylongshore

Overview

Provision Vertex AI infrastructure with Terraform (endpoints, deployed models, vector search indices, pipelines) with production guardrails: encryption, autoscaling, IAM least privilege, and operational validation steps. Use this skill to generate a minimal working Terraform baseline and iterate toward enterprise-ready deployments.

Prerequisites

Before using this skill, ensure:

Google Cloud project with Vertex AI API enabled
Terraform 1.0+ installed
gcloud CLI authenticated with appropriate permissions
Understanding of Vertex AI services and ML models
KMS keys created for encryption (if required)
GCS buckets for model artifacts and embeddings

Instructions

Define AI Services: Identify required Vertex AI components (endpoints, vector search, pipelines)
Configure Terraform: Set up backend and define project variables
Provision Endpoints: Deploy Gemini or custom model endpoints with auto-scaling
Set Up Vector Search: Create indices for embeddings with appropriate dimensions
Configure Encryption: Apply KMS encryption to endpoints and data
Implement Monitoring: Set up Cloud Monitoring for model performance
Apply IAM Policies: Grant least privilege access to AI services
Validate Deployment: Test endpoints and verify model availability

Output

Configuration files or code changes applied to the project
Validation report confirming correct implementation
Summary of changes made and their rationale

See Terraform implementation details for output format specifications.

Error Handling

See ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error handling.

Examples

See ${CLAUDE_SKILL_DIR}/references/examples.md for detailed examples.

Resources

Vertex AI Terraform: https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/vertex_ai_endpoint
Vertex AI documentation: https://cloud.google.com/vertex-ai/docs
Model Garden: https://cloud.google.com/model-garden
Vector Search guide:
Terraform examples in ${CLAUDE_SKILL_DIR}/vertex-examples/

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/jeremylongshore-tons-of-skills-marketplace-vertex-infra-expert/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

jeremylongshore-tons-of-skills-marketplace-vertex-infra-expert.ocm.jsonjson

{
  "ocm": "1",
  "id": "jeremylongshore-tons-of-skills-marketplace-vertex-infra-expert",
  "kind": "skill",
  "name": "vertex-infra-expert",
  "description": "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.",
  "publisher": "jeremylongshore",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "devops",
      "deployment",
      "terraform",
      "ml",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "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."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/jeremylongshore/tons-of-skills-marketplace",
      "path": "skills/.curated/vertex-infra-expert/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/jeremylongshore/tons-of-skills-marketplace/blob/HEAD/skills/.curated/vertex-infra-expert/SKILL.md",
      "key": "jeremylongshore/tons-of-skills-marketplace/skills/.curated/vertex-infra-expert/SKILL.md"
    },
    "compatibility": "Designed for Claude Code",
    "allowed_tools": [
      "Read,",
      "Write,",
      "Edit,",
      "Grep,",
      "Glob,",
      "Bash(terraform:*),",
      "Bash(gcloud:*)"
    ],
    "license": "MIT"
  },
  "instructions": "# Vertex Infra Expert\n\n## Overview\n\nProvision Vertex AI infrastructure with Terraform (endpoints, deployed models, vector search indices, pipelines) with production guardrails: encryption, autoscaling, IAM least privilege, and operational validation steps. Use this skill to generate a minimal working Terraform baseline and iterate toward enterprise-ready deployments.\n\n## Prerequisites\n\nBefore using this skill, ensure:\n\n- Google Cloud project with Vertex AI API enabled\n- Terraform 1.0+ installed\n- gcloud CLI authenticated with appropriate permissions\n- Understanding of Vertex AI services and ML",
  "cost": {
    "context_tokens": 533
  }
}

Fetch it by URL: GET /api/v1/registry/jeremylongshore-tons-of-skills-marketplace-vertex-infra-expert/manifest?version=1.0.0

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