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003-jeremy-vertex-ai-media-master

Comprehensive Google Vertex AI multimodal mastery for Jeremy - video processing (6+ hours), audio generation, image creation with Gemini 2.0/2.5 and Imagen 4. Marketing campaign automation, content generation, and media asset production.

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■ INSTALL // npx @self.md/cli install 003-jeremy-vertex-ai-media-master
AuthorJeremy Longshore
Namespace@jeremylongshore/claude-code-plugins-plus
Category#productivity
Version1.0.0
Stars★ 1,193
Downloads↓ 2
Verification[ ✓ ] self.md verified

Comprehensive Google Vertex AI multimodal mastery for Jeremy - video processing (6+ hours), audio generation, image creation with Gemini 2.0/2.5 and Imagen 4. Marketing campaign automation, content generation, and media asset production.

Installation

npx claude-plugins install @jeremylongshore/claude-code-plugins-plus/003-jeremy-vertex-ai-media-master

Contents

Folders: commands, skills

Files: LICENSE, README.md

Documentation

Comprehensive Google Vertex AI multimodal mastery for video processing, audio generation, image creation, and marketing automation.

Version Category Google Cloud

🎯 Purpose

This plugin makes Claude Code an expert in Google Vertex AI’s multimodal capabilities, with automatic activation for video, audio, image, and text processing workflows focused on marketing applications.

✨ Key Features

🎥 Video Processing (Gemini 2.0/2.5)

  • Process videos up to 6 hours at low resolution
  • 2M context window for massive content
  • Multi-video analysis in single requests
  • Audio track transcription and analysis
  • Marketing insights extraction

🎵 Audio Generation (Lyria Model)

  • Background music composition
  • Voiceover generation
  • Speech-to-text transcription
  • Audio ads and radio spots
  • Multilingual voiceovers

🖼️ Image Generation (Imagen 4)

  • Highest quality text-to-image
  • Interleaved image generation with Gemini 2.5 Flash Image
  • Personalized ad images (Adios approach)
  • Product visualization
  • Campaign asset generation

📢 Marketing Automation

  • ViGenAiR: Convert long videos to short formats automatically
  • Adios: Generate personalized ad images
  • Multi-channel campaign creation
  • Content pipeline automation
  • Product catalog enrichment

🚀 Installation

# Install the plugin
/plugin install 003-jeremy-vertex-ai-media-master@claude-code-plugins-plus

📋 Components

Agent Skills (1)

  • vertex-media-master - Auto-activates for all Vertex AI multimodal operations

Slash Commands (1)

  • /vertex-campaign - Generate complete multimodal marketing campaigns

💡 Usage Examples

Generate Marketing Campaign

/vertex-campaign

Product: Premium wireless earbuds
Audience: Fitness enthusiasts, 25-40
Goal: Product launch
Budget: $30K

Generates:

  • 15+ product images
  • Video scripts (multiple lengths)
  • Background music
  • Email sequences
  • Social media content
  • Blog posts
  • Ad copy

Process Long-Form Video

"Analyze this 4-hour webinar video and extract key highlights for social media clips"

Auto-activates skill and:

  • Processes full video (up to 6 hours)
  • Extracts key moments
  • Generates short-form clips
  • Creates captions
  • Suggests distribution strategy

Generate Personalized Ads

"Create 50 variations of this product ad, personalized for different audience segments"

Auto-generates:

  • Demographic-specific imagery
  • Localized copy
  • Platform-optimized formats
  • A/B test variations

🔧 Technical Implementation

Prerequisites

# Google Cloud setup
gcloud auth application-default login
export GOOGLE_CLOUD_PROJECT="your-project-id"

# Install SDK
pip install google-cloud-aiplatform[vision,audio] google-generativeai

API Integration

from google.cloud import aiplatform
from vertexai.preview.generative_models import GenerativeModel

# Initialize
aiplatform.init(project="your-project", location="us-central1")

# Gemini 2.5 Pro for video
model = GenerativeModel("gemini-2.5-pro")
response = model.generate_content([
    "Analyze this video for marketing insights",
    video_file  # Up to 6 hours
])

🎯 Marketing Use Cases

1. Campaign Asset Production

  • Generate all assets from single brief
  • Consistent brand messaging
  • Multi-channel distribution
  • Cost: ~$5-7 per campaign

2. Video Repurposing

  • Long-form to short-form conversion
  • Platform-specific formatting
  • Automatic captioning
  • Highlight extraction

3. Personalized Content at Scale

  • Audience-specific variations
  • Localized campaigns
  • Dynamic product placement
  • Real-time adaptation

4. Content Automation Pipeline

  • Scheduled asset generation
  • Approval workflows
  • Multi-language support
  • Performance tracking

💰 Cost Optimization

Pricing:

  • Gemini 2.5 Pro: $3.50/1M input tokens
  • Imagen 4: $0.04/image
  • Lyria audio: Variable by duration

Best Practices:

  • Use Gemini Flash for faster ops
  • Batch image requests
  • Cache video embeddings
  • Monitor quota usage

📊 Success Metrics

Track:

  • Asset generation speed (target: 5 images/min)
  • Content approval rate (target: >80%)
  • Personalization scale (target: 1000+ variants)
  • Cost per asset (target: <$0.10/image)
  • Time savings (target: 90% vs manual)

🔗 Integration Points

Google Cloud Services:

  • Cloud Storage (asset management)
  • BigQuery (analytics)
  • Cloud Functions (automation)
  • Vertex AI Pipelines (workflows)

Marketing Platforms:

  • Google Ads (PMax)
  • Meta Business Suite
  • LinkedIn Campaign Manager
  • HubSpot/Marketo
  • WordPress/Contentful

📚 Documentation

Official Resources:

  • [Vertex AI Multimodal](https://clou

Included Skills

This plugin includes 1 skill definition:

vertex-ai-media-master

|

View skill definition

Vertex Ai Media Master

Overview

This skill provides automated assistance for the described functionality.

Prerequisites

  • Access to project files in {baseDir}/
  • Required tools and dependencies installed
  • Understanding of skill functionality
  • Permissions for file operations

Instructions

  1. Identify skill activation trigger and context
  2. Gather required inputs and parameters
  3. Execute skill workflow systematically
  4. Validate outputs meet requirements
  5. Handle errors and edge cases appropriately
  6. Provide clear results and next steps

Output

  • Primary deliverables based on skill purpose
  • Status indicators and success metrics
  • Generated files or configurations
  • Reports and summaries as applicable
  • Recommendations for follow-up actions

Error Handling

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

Examples

See {baseDir}/references/examples.md for detailed examples.

Resources

  • Official documentation for related tools
  • Best practices guides
  • Example use cases and templates
  • Community forums and support channels

Source

View on GitHub