Content Creation

Automated content generation workflows using SkinFlow's multi-agent system.

Overview

This example demonstrates how to build content creation pipelines that leverage multiple specialized agents for different aspects of content production.

Use Cases

• Blog Post Generation: Research, outline, write, and edit blog content
• Social Media Content: Create posts for different platforms
• Technical Documentation: Generate and format technical guides
• Marketing Copy: Write product descriptions and promotional content
• Creative Writing: Stories, scripts, and creative content

Architecture

The content creation system uses:

1. Research Agent: Gathers information and sources
2. Planning Agent: Creates content structure and outlines
3. Writing Agent: Generates initial draft content
4. Editing Agent: Refines and improves the content
5. Formatting Agent: Applies final formatting and styling

Setup

cd examples/content-creation
npm install
cp env.example .env

Basic Usage

Simple Content Generation

import { createMultiAgentFramework } from 'skingflow'

const framework = await createMultiAgentFramework({
  llm: {
    provider: 'openai',
    apiKey: process.env.OPENAI_API_KEY,
    model: 'gpt-4'
  }
})

// Generate a blog post
const result = await framework.processRequest(
  "Write a comprehensive blog post about the benefits of remote work",
  { userId: 'content-creator' }
)

Structured Content Workflow

// Define a content creation workflow
const contentWorkflow = {
  type: 'blog_post',
  topic: 'Sustainable Technology',
  requirements: {
    wordCount: 1500,
    tone: 'informative',
    includeImages: true,
    seoOptimized: true
  }
}

const result = await framework.processRequest(
  `Create content based on this workflow: ${JSON.stringify(contentWorkflow)}`,
  { userId: 'content-team' }
)

Advanced Features

Multi-Platform Content

// Generate content for multiple platforms
const platforms = ['blog', 'twitter', 'linkedin', 'instagram']

for (const platform of platforms) {
  const platformContent = await framework.processRequest(
    `Adapt the main content for ${platform} platform`,
    {
      userId: 'social-media-manager',
      context: { originalContent: result.content, platform }
    }
  )
}

Content Optimization

// SEO optimization
const seoResult = await framework.processRequest(
  "Optimize this content for SEO and suggest improvements",
  {
    userId: 'seo-specialist',
    context: { content: result.content }
  }
)

Templates and Workflows

Blog Post Template

const blogPostTemplate = {
  structure: [
    'introduction',
    'main_points',
    'examples',
    'conclusion',
    'call_to_action'
  ],
  requirements: {
    minimumWords: 800,
    maximumWords: 2000,
    includeHeadings: true,
    addMetaDescription: true
  }
}

Social Media Template

const socialMediaTemplate = {
  platforms: {
    twitter: { maxLength: 280, hashtags: 3 },
    linkedin: { maxLength: 1300, professional: true },
    instagram: { maxLength: 2200, visualContent: true }
  }
}

Quality Control

Content Review Process

// Review and edit content
const reviewResult = await framework.processRequest(
  "Review this content for grammar, clarity, and accuracy",
  {
    userId: 'editor',
    context: { content: draftContent, reviewType: 'comprehensive' }
  }
)

Plagiarism Check

// Check for originality
const originalityResult = await framework.processRequest(
  "Check this content for originality and suggest improvements",
  {
    userId: 'quality-assurance',
    context: { content: finalContent }
  }
)

Integration Examples

CMS Integration

// Publish to content management system
async function publishToCMS(content, metadata) {
  const formattedContent = await framework.processRequest(
    "Format this content for CMS publication",
    {
      userId: 'cms-publisher',
      context: { content, metadata, cmsType: 'wordpress' }
    }
  )

  // Implement CMS publishing logic
  return await cmsClient.publish(formattedContent.content)
}

Analytics Integration

// Generate performance reports
const analyticsResult = await framework.processRequest(
  "Analyze content performance and suggest improvements",
  {
    userId: 'content-analyst',
    context: {
      content: publishedContent,
      metrics: pageViews,
      engagement: userInteractions
    }
  }
)

Best Practices

1. Define Clear Requirements: Specify content goals, audience, and format
2. Use Multiple Review Cycles: Iterate on content for quality improvement
3. Maintain Brand Voice: Ensure consistency across all content
4. Optimize for Platform: Tailor content for specific platforms
5. Monitor Performance: Track content effectiveness and user engagement

Performance Metrics

Content Quality Indicators

• Readability Score: Flesch-Kincaid grade level
• Engagement Rate: Time on page and interaction metrics
• Conversion Rate: Call-to-action effectiveness
• SEO Performance: Search rankings and organic traffic

Workflow Efficiency

• Generation Time: Content creation speed
• Revision Cycles: Number of edits needed
• Resource Usage: Computational cost per content piece

Troubleshooting

Common Issues

1. Inconsistent Quality: Implement standardized review processes
2. Generation Delays: Optimize prompts and agent coordination
3. Brand Voice Issues: Create detailed style guides and examples
4. Platform Adaptation: Develop platform-specific templates

Solutions

• Use content templates for consistency
• Implement quality check workflows
• Create brand voice guidelines
• Develop platform-specific formatting rules

Related Examples

• Intelligent Assistant - General AI assistant capabilities
• Data Analysis - Content performance analysis
• Quick Start - Basic framework usage

Next Steps

• Explore custom tool development for content-specific needs
• Implement A/B testing for content optimization
• Set up content performance monitoring and analytics