AI Content Generation

AI-powered content and image generation skill using the content-image-generation MCP server. This skill provides capabilities for generating marketing content with Claude Sonnet 4 or Gemini 2.0 Pro, creating images with Google Imagen 3/4, and generating videos with Google Veo 2/3.

Core Capabilities

Image Generation

• Generate images with Google Imagen 3 or Imagen 4

• Support multiple aspect ratios (1:1, 16:9, 4:3, 9:16, custom)

• Quality control (SD or HD)

• Batch generation for multiple images

• Prompt enhancement for better results

• Custom negative prompts for quality control

• Seed-based reproducibility

Content Generation

• Marketing content with Claude Sonnet 4 or Gemini 2.0 Pro

• Hero section copy and landing page content

• Blog posts and articles

• Product descriptions and feature lists

• Email campaigns and ad copy

• SEO-optimized content

• Tone and style customization

Video Generation

• Short-form videos with Google Veo 2 or Veo 3

• Multiple aspect ratios and durations

• Prompt-based video creation

• Quality and format options

Cost Optimization

• Pre-generation cost estimation

• Batch optimization recommendations

• Quality vs cost tradeoffs

• Token usage tracking

Instructions

Setup and Validation

Before generating content, verify MCP integration:

Validate MCP server configuration

bash scripts/validate-mcp-setup.sh

Setup environment variables

bash scripts/setup-environment.sh

Image Generation Workflow

Enhance Prompt: Use prompt enhancement for better results

bash scripts/enhance-image-prompt.sh "your basic prompt"

Estimate Cost: Calculate generation costs

bash scripts/calculate-cost.sh --type image --quality HD --count 5

Generate Image: Use MCP tool with enhanced parameters

• Read template: templates/typescript/image-generation.ts or templates/python/image-generation.py

• Call MCP tool: generate_image_imagen3 or batch_generate_images

• Save to assets directory

Validate Output: Check image quality and dimensions

bash scripts/validate-output.sh --type image --path /path/to/image.png

Content Generation Workflow

Define Requirements: Gather content parameters

• Content type (hero, blog, product, email)

• Topic and keywords

• Tone and style (professional, casual, technical)

• Target audience

• Desired length

Estimate Cost: Calculate generation costs

bash scripts/calculate-cost.sh --type content --model claude-sonnet-4 --length 1000

Generate Content: Use MCP tool

• Read template: templates/typescript/content-generation.ts or templates/python/content-generation.py

• Call MCP tool: generate_marketing_content

• Save to content directory

Review and Refine: Validate content quality

bash scripts/validate-output.sh --type content --path /path/to/content.md

Video Generation Workflow

Prepare Prompt: Create detailed video description

bash scripts/enhance-video-prompt.sh "your video description"

Estimate Cost: Calculate video generation costs

bash scripts/calculate-cost.sh --type video --duration 5 --quality HD

Generate Video: Use MCP tool

• Read template: templates/typescript/video-generation.ts or templates/python/video-generation.py

• Call MCP tool: generate_video_veo3

• Save to assets directory

Batch Operations

For multiple assets, use batch generation:

Optimize batch parameters

bash scripts/optimize-batch.sh --type image --count 10 --budget 50

Generate batch with optimized settings

Use batch_generate_images MCP tool

MCP Tools Reference

Image Generation

generate_image_imagen3 : Generate single image with Imagen 3/4

• Parameters: prompt, negative_prompt, aspect_ratio, quality, model, seed

• Returns: Base64 image data, metadata, cost

batch_generate_images : Generate multiple images efficiently

• Parameters: prompts array, shared settings, batch_size

• Returns: Array of images with metadata

Content Generation

• generate_marketing_content : Generate marketing copy

• Parameters: topic, content_type, tone, style, length, model, keywords

• Returns: Generated content, metadata, cost

Video Generation

• generate_video_veo3 : Generate video with Veo 2/3

• Parameters: prompt, duration, aspect_ratio, quality, model

• Returns: Video data, metadata, cost

Utilities

calculate_cost_estimate : Estimate generation costs

• Parameters: operation_type, parameters, quantity

• Returns: Cost breakdown, recommendations

image_prompt_enhancer : Enhance image prompts

• Parameters: basic_prompt, style, quality_level

• Returns: Enhanced prompt, suggestions

Scripts Reference

All scripts are located in skills/ai-content-generation/scripts/ :

• setup-environment.sh : Configure environment variables and credentials

• validate-mcp-setup.sh : Verify MCP server connection and tools

• enhance-image-prompt.sh : Improve image generation prompts

• calculate-cost.sh : Estimate generation costs before execution

• validate-output.sh : Check quality of generated assets

• optimize-batch.sh : Optimize batch generation parameters

• test-generation.sh : Run test generation to verify setup

Templates Reference

TypeScript Templates (templates/typescript/ )

• image-generation.ts : Complete image generation implementation

• content-generation.ts : Marketing content generation

• video-generation.ts : Video generation workflow

Python Templates (templates/python/ )

• image-generation.py : Complete image generation implementation

• content-generation.py : Marketing content generation

• video-generation.py : Video generation workflow

Examples

See examples/ directory for comprehensive usage examples:

• basic-usage.md : Simple image and content generation

• advanced-usage.md : Batch operations, cost optimization, custom parameters

• common-patterns.md : Hero images, blog headers, product galleries

• error-handling.md : Retry logic, fallbacks, validation

• integration.md : Astro integration, asset management, workflow automation

Best Practices

Image Generation

• Always enhance prompts for better quality

• Use HD quality for hero sections and key visuals

• Use SD quality for thumbnails and secondary images

• Specify negative prompts to avoid unwanted elements

• Use consistent seeds for reproducible results

• Batch similar images to optimize costs

Content Generation

• Provide clear topic and keywords

• Specify target audience for better relevance

• Choose appropriate tone and style

• Review and customize generated content

• Use Claude for technical/detailed content

• Use Gemini for creative/marketing content

Cost Optimization

• Estimate costs before generation

• Use batch operations for multiple assets

• Choose SD quality when HD is not required

• Optimize prompt length for content generation

• Cache and reuse similar assets

• Monitor token usage and costs

Error Handling

• Validate MCP setup before operations

• Check API quotas and limits

• Implement retry logic for transient failures

• Validate output quality after generation

• Log costs and metadata for tracking

Requirements

Environment Variables

• GOOGLE_CLOUD_PROJECT : Google Cloud project ID for Vertex AI

• ANTHROPIC_API_KEY : API key for Claude Sonnet content generation

• GOOGLE_AI_API_KEY : (Optional) API key for Gemini content generation

MCP Configuration

• content-image-generation MCP server must be configured in .mcp.json

• Google Cloud credentials must be set up for Vertex AI

• Appropriate APIs must be enabled (Vertex AI, Imagen, Veo)

Project Structure

• Assets directory for storing generated images/videos

• Content directory for storing generated text

• Environment file for API credentials

Skill Version: 1.0.0 Plugin: website-builder MCP Server: content-image-generation