vertex-ai-endpoint-config
Vertex Ai Endpoint Config - Auto-activating skill for GCP Skills. Triggers on: vertex ai endpoint config, vertex ai endpoint config Part of the GCP Skills skill category.
Overall
score
24%
Does it follow best practices?
Validation for skill structure
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill vertex-ai-endpoint-configActivation
22%This description is severely lacking in substance. It fails to explain what the skill actually does with Vertex AI endpoints (e.g., create, configure, deploy, monitor) and provides only repetitive trigger terms without natural language variations. The description reads more like a placeholder than a functional skill description.
Suggestions
Add specific actions the skill performs, e.g., 'Creates and configures Vertex AI endpoints for model deployment, manages traffic splitting, and sets up prediction routing.'
Add a 'Use when...' clause with natural trigger scenarios, e.g., 'Use when deploying ML models to GCP, setting up inference endpoints, or configuring model serving infrastructure.'
Include natural keyword variations users might say: 'model deployment', 'inference endpoint', 'prediction service', 'deploy to Vertex', 'GCP model hosting'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions - only 'Auto-activating skill for GCP Skills' which is vague and abstract. No specific capabilities like 'configure endpoints', 'deploy models', or 'manage traffic splitting' are mentioned. | 1 / 3 |
Completeness | The 'what' is essentially missing - we don't know what this skill actually does beyond vague association with Vertex AI endpoints. The 'when' only repeats the skill name as triggers without explaining use cases. | 1 / 3 |
Trigger Term Quality | Contains 'vertex ai endpoint config' as a trigger term which is relevant but technical. Missing natural variations users might say like 'deploy model', 'endpoint deployment', 'model serving', 'inference endpoint', or 'GCP ML deployment'. | 2 / 3 |
Distinctiveness Conflict Risk | The 'vertex ai endpoint config' trigger is somewhat specific to a GCP service, but without describing actual capabilities, it could conflict with other Vertex AI or GCP-related skills. The generic 'GCP Skills' category reference adds ambiguity. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
0%This skill content is a placeholder template with no actual technical substance. It contains only meta-descriptions of what the skill claims to do without providing any concrete guidance on Vertex AI endpoint configuration. The content fails all dimensions because it lacks executable code, specific commands, actual workflows, or any real information about GCP Vertex AI.
Suggestions
Add concrete, executable code examples for common Vertex AI endpoint configuration tasks (e.g., creating an endpoint, deploying a model, configuring traffic split)
Include specific gcloud CLI commands or Terraform/Python SDK snippets that are copy-paste ready
Define a clear workflow with validation steps for endpoint deployment (e.g., create endpoint -> deploy model -> verify deployment -> test prediction)
Replace the generic capability descriptions with actual technical content covering endpoint types, machine types, scaling configurations, and common configuration patterns
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely boilerplate with no actual technical information about Vertex AI endpoint configuration. It explains what the skill does in generic terms without providing any concrete guidance, wasting tokens on meta-description. | 1 / 3 |
Actionability | No concrete code, commands, or specific instructions are provided. The content only describes what the skill claims to do ('provides step-by-step guidance') without actually providing any guidance, examples, or executable content. | 1 / 3 |
Workflow Clarity | No workflow is defined. Despite claiming to provide 'step-by-step guidance,' there are no actual steps, sequences, or validation checkpoints for configuring Vertex AI endpoints. | 1 / 3 |
Progressive Disclosure | No structure for progressive disclosure exists. There are no references to detailed documentation, no links to related files, and no organization of content from basic to advanced. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
69%Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
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 |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 11 / 16 Passed | |
Reviewed
Table of Contents
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