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AGENT SKILL

vertex-media-master

vertex-media-master 是面向数据与分析、内容与媒体的 Agent Skill,来自 jeremylongshore/claude-code-plugins-plus-skills。查看技能说明、操作步骤与使用约定,并通过原项目了解详细用法。

Automatic activation for ALL Google Vertex AI multimodal operations - video processing, audio generation, image creation, and marketing campaigns. **TRIGGER PHRASES:** - "vertex ai", "gemini multimodal", "process video", "generate audio", "create images", "marketing campaign" - "imagen", "video understanding", "multimodal", "content generation", "media assets" **AUTO-INVOKES FOR:** - Video processing and understanding (up to 6 hours) - Audio generation and transcription - Image generation with Imagen 4 - Marketing campaign automation - Social media content creation - Ad creative generation - Multimodal content workflows

SKILL.md

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nameVertex AI Media Master
descriptionAutomatic activation for ALL Google Vertex AI multimodal operations - video processing, audio generation, image creation, and marketing campaigns. **TRIGGER PHRASES:** - "vertex ai", "gemini multimodal", "process video", "generate audio", "create images", "marketing campaign" - "imagen", "video understanding", "multimodal", "content generation", "media assets" **AUTO-INVOKES FOR:** - Video processing and understanding (up to 6 hours) - Audio generation and transcription - Image generation with Imagen 4 - Marketing campaign automation - Social media content creation - Ad creative generation - Multimodal content workflows
allowed-toolsRead, Write, Edit, Grep, Glob, Bash
version1.0.0

Vertex AI Media Master - Comprehensive Multimodal AI Operations

This Agent Skill provides comprehensive mastery of Google Vertex AI multimodal capabilities for video, audio, image, and text processing with focus on marketing applications.

Core Capabilities

🎥 Video Processing (Gemini 2.0/2.5)

  • Video Understanding: Process videos up to 6 hours at low resolution or 2 hours at default resolution
  • 2M Context Window: Gemini 2.5 Pro handles massive video content
  • Audio Track Processing: Automatic audio transcription from video
  • Multi-video Analysis: Process multiple videos in single request
  • Video Summarization: Extract key moments, scenes, and insights
  • Marketing Use Cases:
  • Analyze competitor video ads
  • Extract highlights from long-form content
  • Generate video summaries for social media
  • Transcribe and caption video content
  • Identify brand mentions and product placements

🎵 Audio Generation & Processing

  • Lyria Model (2025): Native audio and music generation
  • Speech-to-Text: Transcribe audio with speaker diarization
  • Text-to-Speech: Generate natural voiceovers
  • Music Composition: Background music for campaigns
  • Audio Enhancement: Noise reduction and quality improvement
  • Marketing Use Cases:
  • Generate podcast scripts and voiceovers
  • Create audio ads and radio spots
  • Produce background music for video campaigns
  • Transcribe customer interviews
  • Generate multilingual voiceovers

🖼️ Image Generation (Imagen 4 & Gemini 2.5 Flash Image)

  • Imagen 4: Highest quality text-to-image generation
  • Gemini 2.5 Flash Image: Interleaved image generation with text
  • Style Transfer: Apply brand styles to generated images
  • Product Visualization: Generate product mockups
  • Campaign Assets: Create ad creatives and social media graphics
  • Marketing Use Cases:
  • Generate personalized ad images (Adios solution)
  • Create social media graphics at scale
  • Produce product lifestyle images
  • Generate A/B test variations
  • Create branded campaign visuals

📢 Marketing Campaign Automation

  • ViGenAiR: Convert long-form video ads to short formats automatically
  • Adios: Generate personalized ad images tailored to audience context
  • Campaign Asset Generation: Photos, soundtracks, voiceovers from prompts
  • Content Pipeline: Email copy, blog posts, social media, PMax assets
  • Catalog Enrichment: Multi-agent workflow for product onboarding
  • Marketing Use Cases:
  • Automated campaign asset production
  • Personalized content at scale
  • Multi-channel content distribution
  • Product catalog enhancement
  • Visual merchandising automation

🔧 Technical Implementation

API Integration:

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

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

# Gemini 2.5 Pro for video
model = GenerativeModel("gemini-2.5-pro")

# Process video with audio
response = model.generate_content([
    "Analyze this video and extract key marketing insights",
    video_file,  # Up to 6 hours
])

# Imagen 4 for image generation
from vertexai.preview.vision_models import ImageGenerationModel
imagen = ImageGenerationModel.from_pretrained("imagen-4")
images = imagen.generate_images(
    prompt="Professional product photo, studio lighting, white background",
    number_of_images=4
)

Gemini 2.5 Flash Image (Interleaved Generation):

# Generate images within text responses
model = GenerativeModel("gemini-2.5-flash-image")
response = model.generate_content([
    "Create a 5-step recipe with images for each step"
])
# Returns text + images interleaved

Audio Generation (Lyria):

from vertexai.preview.audio_models import AudioGenerationModel
lyria = AudioGenerationModel.from_pretrained("lyria")
audio = lyria.generate_audio(
    prompt="Upbeat background music for product launch video, 30 seconds",
    duration=30
)

📊 Marketing Workflow Automation

1. Multi-Channel Campaign Creation:

# Single prompt generates all assets
campaign = model.generate_content([
    """Create a product launch campaign for [product]:
    - Hero image (1920x1080)
    - 3 social media graphics (1080x1080)
    - 30-second video script
    - Background music description
    - Email marketing copy
    - Instagram caption"""
])

2. Video Repurposing Pipeline:

# Long-form to short-form conversion (ViGenAiR approach)
long_video = "gs://bucket/original-ad-60s.mp4"
response = model.generate_content([
    f"Extract 3 engaging 15-second clips from this video for TikTok/Reels",
    long_video
])
# Auto-generates format-specific versions

3. Personalized Ad Generation:

# Context-aware image generation (Adios approach)
for audience in audiences:
    ad_image = imagen.generate_images(
        prompt=f"Product ad for {product}, targeting {audience.demographics}, {audience.style_preference}",
        aspect_ratio="16:9"
    )

🎯 Best Practices for Jeremy

1. Project Setup:

# Set environment variables
export GOOGLE_CLOUD_PROJECT="your-project-id"
export GOOGLE_APPLICATION_CREDENTIALS="path/to/service-account.json"

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

2. Rate Limits & Quotas: - Gemini 2.5 Pro: 2M tokens/min (video processing) - Imagen 4: 100 images/min - Monitor usage in Cloud Console

3. Cost Optimization: - Use Gemini 2.5 Flash for faster, cheaper operations - Batch image generation requests - Cache video embeddings for repeated analysis - Use low-resolution video setting when appropriate

4. Security & Compliance: - Keep API keys in Secret Manager, never in code - Use service accounts with minimal permissions - Enable VPC Service Controls for data residency - Log all API calls for audit trails

🚀 Advanced Marketing Use Cases

1. Campaign Performance Analysis:

# Analyze competitor campaigns
competitor_videos = ["gs://bucket/competitor1.mp4", "gs://bucket/competitor2.mp4"]
analysis = model.generate_content([
    "Compare these competitor videos: themes, messaging, CTAs, production quality",
    *competitor_videos
])

2. Content Localization:

# Generate multilingual campaigns
for lang in ["en", "es", "fr", "de", "ja"]:
    localized_content = model.generate_content([
        f"Translate and culturally adapt this campaign for {lang} market:",
        campaign_brief,
        hero_image
    ])

3. A/B Test Generation:

# Generate variations automatically
variations = []
for style in ["minimalist", "bold", "luxury", "playful"]:
    variation = imagen.generate_images(
        prompt=f"Product ad, {style} style, {brand_guidelines}",
        number_of_images=1
    )
    variations.append(variation)

📚 Reference Documentation

Official Documentation: - Vertex AI Multimodal: https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/overview - Gemini 2.5 Pro: https://cloud.google.com/vertex-ai/generative-ai/docs/models - Imagen 4: https://cloud.google.com/vertex-ai/generative-ai/docs/image/overview - Video Understanding: https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/video-understanding

Marketing Solutions: - GenAI for Marketing: https://github.com/GoogleCloudPlatform/genai-for-marketing - ViGenAiR (video repurposing) - Adios (personalized ad images)

Pricing: - Gemini 2.5 Pro: $3.50/1M input tokens, $10.50/1M output tokens - Imagen 4: $0.04/image - Video processing: Included in Gemini token pricing

When This Skill Activates

This skill automatically activates when you mention: - Video processing, analysis, or understanding - Audio generation, music composition, or voiceovers - Image generation, ad creatives, or visual content - Marketing campaigns, content automation, or asset production - Gemini multimodal capabilities - Vertex AI media operations - Social media content, email marketing, or PMax campaigns

Integration with Other Tools

Google Cloud Services: - Cloud Storage for media asset management - BigQuery for campaign analytics - Cloud Functions for automation triggers - Vertex AI Pipelines for content workflows

Third-Party Integrations: - Social media APIs (LinkedIn, Twitter, Instagram) - Marketing automation platforms (HubSpot, Marketo) - CMS integrations (WordPress, Contentful) - DAM systems (Bynder, Cloudinary)

Success Metrics

Track These KPIs: - Asset generation speed (baseline: 5 images/min) - Content approval rate (target: >80%) - Campaign personalization scale (target: 1000+ variants) - Cost per asset (target: <$0.10/image) - Time saved vs manual production (target: 90% reduction)


This skill makes Jeremy a Vertex AI multimodal expert with instant access to video processing, audio generation, image creation, and marketing automation capabilities.

来源:jeremylongshore/claude-code-plugins-plus-skills · MIT 许可 · 许可原文 · MD 为来源页保存的历史版本