vertex-infra-expert
tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill vertex-infra-expertExecute 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.
Validation
81%| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 13 / 16 Passed | |
Implementation
22%This skill provides a skeletal outline for Vertex AI Terraform provisioning but lacks the concrete, executable content needed to be useful. It describes what should be done at a high level without providing any actual Terraform code, specific commands, or validation procedures. The empty Output section and placeholder references suggest this is an incomplete template rather than a functional skill.
Suggestions
Add concrete Terraform code examples for at least one core resource (e.g., google_vertex_ai_endpoint) with proper configuration for encryption and auto-scaling
Include specific terraform commands with validation checkpoints: terraform init -> terraform plan -> review -> terraform apply -> verify with gcloud commands
Populate the Output section with expected terraform output values and how to verify successful deployment
Replace vague instructions like 'Configure Terraform' with actual backend configuration code and variable definitions
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is relatively brief but includes some unnecessary padding like the verbose overview and prerequisites that Claude would already know (e.g., 'Understanding of Vertex AI services and ML models'). The instructions section is high-level without adding much value. | 2 / 3 |
Actionability | The skill provides only vague, abstract guidance with no concrete Terraform code, commands, or executable examples. Instructions like 'Configure Terraform' and 'Provision Endpoints' describe rather than instruct, offering no copy-paste ready content. | 1 / 3 |
Workflow Clarity | While steps are numbered, they lack any validation checkpoints, feedback loops, or specific commands. For infrastructure provisioning (a potentially destructive operation), there's no terraform plan/apply sequence, no validation steps, and the 'Validate Deployment' step has no concrete guidance. | 1 / 3 |
Progressive Disclosure | The skill references external files for errors and examples which is good structure, but the main content is too thin to serve as a useful overview. The Output section is completely empty, and the references use placeholder paths ({baseDir}) without clear context. | 2 / 3 |
Total | 6 / 12 Passed |
Activation
100%This is a strong skill description that excels across all dimensions. It provides specific capabilities (Model Garden, Gemini endpoints, vector search, ML pipelines), explicit trigger phrases that users would naturally say, and clear guidance on when to use it. The combination of Vertex AI + Terraform creates a distinct niche with minimal conflict risk.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Provisions Model Garden models, Gemini endpoints, vector search indices, ML pipelines, and production AI services with encryption and auto-scaling.' | 3 / 3 |
Completeness | Clearly answers both what (provisions various Vertex AI components) and when ('use when provisioning Vertex AI infrastructure with Terraform' plus explicit trigger phrases). Has explicit 'Use when' and 'Trigger with phrases' guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'vertex ai terraform', 'deploy gemini terraform', 'model garden infrastructure', 'vertex ai endpoints terraform', 'vector search terraform' - these are specific phrases users would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Very clear niche combining Vertex AI + Terraform specifically. The trigger terms are highly specific to this domain and unlikely to conflict with general Terraform or general AI skills. | 3 / 3 |
Total | 12 / 12 Passed |
Reviewed
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