vertex-ai

Test Vertex AI connectivity and route Veo and Gemini generation requests.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/cgk-platform/cgk --skill vertex-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vertex-ai
Source: https://github.com/cgk-platform/cgk/tree/main/openclaw-skills/vertex-ai
Command: npx skills add https://github.com/cgk-platform/cgk --skill vertex-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires google-genai>=1.0.0, google-api-core>=2.0.0, openai>=1.0.0, requests>=2.31.0, and includes scripts (resource) components.

What problem does it solve?

Vertex AI provides higher rate limits than AI Studio for Veo video generation and Gemini image generation, offering a reliable alternative when limits are reached or when routing to Vertex AI backends is desired.

Core Features & Use Cases

  • High-rate connectivity tests for Veo video and Gemini image generation.
  • Explicit backend routing to Vertex AI and practical fallbacks to avoid quota exhaustion.
  • REST API access guidance and practical model IDs for quick integration.

Quick Start

Run the Vertex AI connectivity tests to verify access and routing.

Frequently Asked Questions about vertex-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I route Veo video generation to Vertex AI when hitting rate limits?

Route Veo video generation to Vertex AI to access higher rate limits than AI Studio. This Skill performs explicit backend routing and connectivity checks to ensure reliable media generation when quota exhaustion occurs.

What is the best way to test Vertex AI connectivity for Gemini image generation?

Test Vertex AI connectivity for Gemini image generation using built-in scripts that verify quota availability and REST API access. This Skill validates environment variables, model IDs, and end-to-end routing for quick integration.

Why does my AI Studio backend fail with quota exhaustion during video generation?

AI Studio imposes lower rate limits that cause quota exhaustion during heavy video generation. Routing requests to Vertex AI backends provides higher rate limits and practical fallbacks to avoid hitting these constraints.

Do I need specific environment variables to route requests to Vertex AI backends?

Yes, routing requests to Vertex AI requires explicit environment variable setup. This Skill verifies necessary environment configurations, model IDs, and REST API references to successfully execute end-to-end connectivity tests.

Can I use the OpenAI library to test Vertex AI connectivity?

Yes, the OpenAI library is included as a dependency alongside google-genai and requests. This Skill leverages these libraries to run connectivity scripts and verify backend routing for Veo and Gemini models.

What are the limitations of using Vertex AI for media generation routing?

Vertex AI media generation routing requires explicit backend configuration and connectivity verification. Users must manage environment variables and model IDs carefully, as failed routing or quota checks will prevent successful generation.