marketing-pipeline-share-content-automation

name	marketing-pipeline-share-content-automation
description	AI-powered content pipeline that auto-researches, generates scripts, and creates videos with Claude/OpenAI and Remotion
triggers	["automate my content creation workflow","generate blog posts from trending topics","create videos from text content automatically","research and write marketing content with AI","build a content automation pipeline","set up AI content generation system","scrape news and generate articles","render videos from blog posts with Remotion"]

Marketing Pipeline Share - AI Content Automation

Skill by ara.so — Marketing Skills collection.

Overview

Marketing Pipeline Share is an all-in-one TypeScript-based content automation system that:

• Auto-researches trending topics by crawling news sources (TechCrunch, Twitter, LinkedIn)
• Generates content in multiple formats (listicles, POV, case studies) using Claude 3/OpenAI
• Renders videos automatically from text using Remotion
• Supports multilingual content (English/Vietnamese) with customizable tone
• Provides end-to-end pipeline from research to publication

This tool transforms a single keyword into full blog posts, social media content, and video assets.

Installation

# Clone the repository
git clone https://github.com/pennydinh/marketing-pineline-share.git
cd marketing-pineline-share

# Install dependencies
npm install
# or
yarn install

# Set up environment variables
cp .env.example .env

Required Environment Variables

# AI Providers
ANTHROPIC_API_KEY=your_claude_api_key
OPENAI_API_KEY=your_openai_api_key

# Data Sources (RapidAPI)
RAPIDAPI_KEY=your_rapidapi_key

# Optional: Custom endpoints
API_BASE_URL=http://localhost:3000

Project Structure

marketing-pineline-share/
├── src/
│   ├── app/              # Next.js app router pages
│   ├── components/       # React components
│   ├── lib/
│   │   ├── ai/          # AI integration (Claude, OpenAI)
│   │   ├── scraper/     # Web scraping modules
│   │   ├── content/     # Content generation logic
│   │   └── video/       # Remotion video rendering
│   └── types/           # TypeScript type definitions
├── remotion/            # Video templates
└── public/              # Static assets

Core Features & Usage

1. Research & Content Scraping

import { researchTopic } from '@/lib/scraper';

// Auto-scrape trending news from multiple sources
async function gatherResearch(keyword: string) {
  const research = await researchTopic({
    keyword,
    sources: ['techcrunch', 'twitter', 'linkedin'],
    timeframe: '24h',
    limit: 20
  });
  
  return {
    articles: research.articles,
    insights: research.insights,
    statistics: research.stats
  };
}

2. AI Content Generation

import { generateContent } from '@/lib/ai/content-generator';

// Generate blog post with Claude/OpenAI
async function createBlogPost(topic: string, research: any) {
  const content = await generateContent({
    provider: 'claude', // or 'openai'
    model: 'claude-3-sonnet-20240229',
    format: 'blog-post', // 'listicle', 'case-study', 'how-to'
    topic,
    research,
    language: 'en', // or 'vi'
    tone: 'professional', // 'friendly', 'humorous'
    length: 'medium' // 'short', 'long'
  });
  
  return {
    title: content.title,
    body: content.body,
    meta: content.metadata,
    images: content.suggestedImages
  };
}

3. Multi-Format Content Generation

import { ContentPipeline } from '@/lib/content/pipeline';

// Generate content in multiple formats from single input
async function generateMultiFormat(keyword: string) {
  const pipeline = new ContentPipeline({
    apiKey: process.env.ANTHROPIC_API_KEY
  });
  
  // Research phase
  await pipeline.research(keyword);
  
  // Generate multiple formats in parallel
  const outputs = await pipeline.generateAll({
    formats: [
      { type: 'blog-post', language: 'en' },
      { type: 'blog-post', language: 'vi' },
      { type: 'social-media', platform: 'linkedin' },
      { type: 'social-media', platform: 'twitter' },
      { type: 'video-script', duration: 60 }
    ]
  });
  
  return outputs;
}

4. Video Generation with Remotion

import { renderVideo } from '@/lib/video/renderer';
import { bundle } from '@remotion/bundler';
import { renderMedia } from '@remotion/renderer';

// Convert blog post to video
async function createVideoFromPost(post: any) {
  const videoConfig = {
    compositionId: 'BlogPostVideo',
    inputProps: {
      title: post.title,
      content: post.body,
      style: 'modern',
      duration: 90 // seconds
    },
    codec: 'h264',
    outputLocation: `./output/${post.slug}.mp4`,
    // Platform-specific ratios
    width: 1080,
    height: 1920 // 9:16 for TikTok/Reels/Shorts
  };
  
  const bundled = await bundle('./src/remotion/index.ts');
  const result = await renderMedia({
    composition: videoConfig,
    serveUrl: bundled,
    codec: 'h264',
    outputLocation: videoConfig.outputLocation
  });
  
  return result;
}

API Endpoints

If running as a Next.js server:

POST /api/research

// Request
{
  "keyword": "AI automation",
  "sources": ["techcrunch", "twitter"],
  "timeframe": "24h"
}

// Response
{
  "articles": [...],
  "insights": [...],
  "trending": true
}

POST /api/generate

// Request
{
  "topic": "AI content automation",
  "format": "blog-post",
  "language": "en",
  "research": {...}
}

// Response
{
  "title": "How AI is Transforming Content Creation",
  "body": "...",
  "metadata": {...},
  "images": [...]
}

POST /api/video/render

// Request
{
  "content": {...},
  "template": "modern",
  "aspectRatio": "9:16"
}

// Response
{
  "videoUrl": "https://...",
  "thumbnail": "https://...",
  "duration": 90
}

Common Patterns

Full Pipeline Example

import { ContentAutomation } from '@/lib/automation';

async function fullContentPipeline(keyword: string) {
  const automation = new ContentAutomation({
    anthropicKey: process.env.ANTHROPIC_API_KEY,
    openaiKey: process.env.OPENAI_API_KEY,
    rapidApiKey: process.env.RAPIDAPI_KEY
  });
  
  // 1. Research
  console.log('🔍 Researching topic...');
  const research = await automation.research(keyword);
  
  // 2. Generate content
  console.log('✍️ Generating content...');
  const content = await automation.generate({
    topic: keyword,
    research,
    formats: ['blog', 'social', 'video-script']
  });
  
  // 3. Create visuals
  console.log('🎬 Rendering video...');
  const video = await automation.renderVideo({
    script: content.videoScript,
    style: 'professional'
  });
  
  // 4. Export all assets
  return {
    blogPost: content.blog,
    socialPosts: content.social,
    video: video.url,
    publishReady: true
  };
}

Scheduled Content Generation

import { CronJob } from 'cron';
import { ContentAutomation } from '@/lib/automation';

// Auto-generate daily content
const dailyContentJob = new CronJob('0 9 * * *', async () => {
  const automation = new ContentAutomation({
    anthropicKey: process.env.ANTHROPIC_API_KEY
  });
  
  const trendingTopics = await automation.getTrendingTopics({
    category: 'marketing',
    count: 3
  });
  
  for (const topic of trendingTopics) {
    const content = await fullContentPipeline(topic);
    await automation.publishToQueue(content);
  }
});

dailyContentJob.start();

Custom Content Templates

import { ContentGenerator } from '@/lib/ai/content-generator';

// Create custom content template
const generator = new ContentGenerator({
  provider: 'claude',
  apiKey: process.env.ANTHROPIC_API_KEY
});

const customTemplate = {
  name: 'product-launch',
  structure: [
    { section: 'hook', prompt: 'Create attention-grabbing opening' },
    { section: 'problem', prompt: 'Describe pain points' },
    { section: 'solution', prompt: 'Introduce product benefits' },
    { section: 'features', prompt: 'List 5 key features' },
    { section: 'cta', prompt: 'Strong call-to-action' }
  ],
  tone: 'exciting',
  length: 800
};

const content = await generator.generateFromTemplate(
  customTemplate,
  { product: 'AI Content Tool', audience: 'marketers' }
);

Configuration

Content Generator Config

// src/config/content.ts
export const contentConfig = {
  ai: {
    defaultProvider: 'claude',
    fallbackProvider: 'openai',
    maxTokens: 4000,
    temperature: 0.7
  },
  research: {
    sources: ['techcrunch', 'twitter', 'linkedin', 'producthunt'],
    maxArticles: 20,
    timeframe: '24h'
  },
  video: {
    defaultDuration: 60,
    outputFormat: 'mp4',
    quality: 'high',
    aspectRatios: {
      tiktok: '9:16',
      youtube: '16:9',
      instagram: '1:1'
    }
  }
};

Remotion Video Config

// src/remotion/config.ts
export const videoConfig = {
  fps: 30,
  durationInFrames: 90 * 30, // 90 seconds
  width: 1080,
  height: 1920,
  compositions: [
    {
      id: 'BlogPostVideo',
      component: BlogPostComposition,
      defaultProps: {
        theme: 'dark',
        animation: 'smooth'
      }
    }
  ]
};

Troubleshooting

API Rate Limits

// Implement retry logic with exponential backoff
import { retry } from '@/lib/utils/retry';

const content = await retry(
  () => generateContent({ topic, research }),
  { maxAttempts: 3, delayMs: 1000 }
);

Video Rendering Errors

# Ensure Remotion CLI is installed
npm install -g @remotion/cli

# Check Remotion dependencies
npx remotion versions

# Common fix: Clear bundle cache
rm -rf .remotion

Research Scraping Issues

// Handle failed scrapes gracefully
try {
  const research = await researchTopic(keyword);
} catch (error) {
  console.warn('Scraping failed, using fallback');
  // Use cached data or alternative source
  const fallback = await getFallbackResearch(keyword);
}

Memory Issues with Large Content

// Process content in chunks
async function processLargeDataset(items: any[]) {
  const chunkSize = 10;
  const results = [];
  
  for (let i = 0; i < items.length; i += chunkSize) {
    const chunk = items.slice(i, i + chunkSize);
    const processed = await Promise.all(
      chunk.map(item => generateContent(item))
    );
    results.push(...processed);
  }
  
  return results;
}

Running the Project

# Development mode
npm run dev

# Build for production
npm run build

# Start production server
npm start

# Render single video (CLI)
npx remotion render BlogPostVideo output.mp4 --props='{"title":"My Post"}'

Best Practices

1. Cache research data to avoid redundant API calls
2. Use queue systems (Bull, BullMQ) for video rendering
3. Implement webhooks for async video completion notifications
4. Store generated content in database for reuse
5. Monitor API usage to stay within rate limits
6. Version control templates for consistent output quality

This skill enables AI agents to help developers build complete content automation workflows with research, generation, and video production capabilities.