marketing-pipeline-automation

Original：🇺🇸 English

Translated

Automate content creation from research to video generation using AI-powered content pipeline with Claude, OpenAI, and Remotion

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Sourcearadotso/marketing-skills

Added on2026-05-29

NPX Install

npx skill4agent add aradotso/marketing-skills marketing-pipeline-automation

SKILL.md Content

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Marketing Pipeline Automation

Skill by ara.so — Marketing Skills collection.

This skill enables AI agents to help developers build and configure an automated content creation pipeline that handles research, scriptwriting, content generation, and video rendering using Claude 3, OpenAI, and Remotion.

What This Project Does

The Marketing Pipeline is an end-to-end content automation system that:

Auto-crawls trending news from sources like TechCrunch, a16z, Twitter/X, LinkedIn (last 24h)
Generates content in multiple formats (Top Lists, POV, Case Studies, How-to) using Claude/OpenAI
Supports bilingual output (English and Vietnamese) with customizable tone
Renders videos automatically from written content using Remotion
Optimizes for platforms like Reels, TikTok, and Shorts

Installation

Prerequisites

bash

# Node.js 18+ required
node --version

# Package manager
npm --version
# or
pnpm --version

Clone and Setup

bash

git clone https://github.com/pennydinh/marketing-pineline-share.git
cd marketing-pineline-share

# Install dependencies
npm install
# or
pnpm install

Environment Configuration

Create a

.env.local

file in the root directory:

bash

# AI Provider Keys
ANTHROPIC_API_KEY=your_claude_api_key
OPENAI_API_KEY=your_openai_api_key

# Research & Crawling APIs
RAPIDAPI_KEY=your_rapidapi_key

# Video Rendering (Remotion)
REMOTION_WEBHOOK_SECRET=your_webhook_secret

# Database (if applicable)
DATABASE_URL=postgresql://user:password@localhost:5432/marketing_pipeline

# Next.js Configuration
NEXT_PUBLIC_API_URL=http://localhost:3000

Key Commands

Development

bash

# Start development server
npm run dev

# Build for production
npm run build

# Start production server
npm run start

# Run linter
npm run lint

Remotion Video Rendering

bash

# Render single video
npm run remotion:render

# Preview Remotion composition
npm run remotion:preview

# Upgrade Remotion
npm run remotion:upgrade

Core Architecture

Project Structure

marketing-pineline-share/
├── src/
│   ├── app/              # Next.js app directory
│   ├── components/       # React components
│   ├── lib/
│   │   ├── ai/          # AI integration (Claude, OpenAI)
│   │   ├── crawlers/    # Content crawling modules
│   │   ├── generators/  # Content generation logic
│   │   └── video/       # Video rendering (Remotion)
│   └── utils/           # Utility functions
├── public/              # Static assets
├── remotion/            # Remotion video templates
└── .env.local          # Environment variables

API Usage Patterns

1. Content Research & Crawling

typescript

// src/lib/crawlers/news-crawler.ts
import axios from 'axios';

interface NewsSource {
  title: string;
  url: string;
  publishedAt: string;
  content: string;
}

export async function crawlTechNews(keyword: string): Promise<NewsSource[]> {
  const options = {
    method: 'GET',
    url: 'https://news-api.p.rapidapi.com/v1/search',
    params: {
      q: keyword,
      lang: 'en',
      sort_by: 'published_at',
      from: new Date(Date.now() - 24 * 60 * 60 * 1000).toISOString(), // Last 24h
    },
    headers: {
      'X-RapidAPI-Key': process.env.RAPIDAPI_KEY!,
      'X-RapidAPI-Host': 'news-api.p.rapidapi.com'
    }
  };

  try {
    const response = await axios.request(options);
    return response.data.articles.slice(0, 10);
  } catch (error) {
    console.error('News crawling error:', error);
    return [];
  }
}

2. AI Content Generation with Claude

typescript

// src/lib/ai/claude-generator.ts
import Anthropic from '@anthropic-ai/sdk';

const anthropic = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY!,
});

interface ContentRequest {
  keyword: string;
  format: 'toplist' | 'pov' | 'case-study' | 'how-to';
  language: 'en' | 'vi';
  tone: 'expert' | 'friendly' | 'humorous';
  researchData: string;
}

export async function generateContentWithClaude(
  request: ContentRequest
): Promise<string> {
  const systemPrompt = `You are an expert content creator specializing in ${request.format} format. 
  Write in ${request.language === 'vi' ? 'Vietnamese' : 'English'} with a ${request.tone} tone.
  Use the provided research data to create data-backed, trending content.`;

  const userPrompt = `Create a ${request.format} article about "${request.keyword}" using this research:
  
${request.researchData}

Requirements:
- Include real data and insights from the research
- Make it engaging and trend-focused
- Optimize for social media sharing
- Add relevant statistics and quotes`;

  const message = await anthropic.messages.create({
    model: 'claude-3-5-sonnet-20241022',
    max_tokens: 4096,
    system: systemPrompt,
    messages: [
      {
        role: 'user',
        content: userPrompt,
      },
    ],
  });

  return message.content[0].type === 'text' ? message.content[0].text : '';
}

3. OpenAI Alternative

typescript

// src/lib/ai/openai-generator.ts
import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY!,
});

export async function generateContentWithOpenAI(
  request: ContentRequest
): Promise<string> {
  const completion = await openai.chat.completions.create({
    model: 'gpt-4-turbo-preview',
    messages: [
      {
        role: 'system',
        content: `You are an expert content creator specializing in ${request.format} format.`,
      },
      {
        role: 'user',
        content: `Create a ${request.format} article about "${request.keyword}" using this research:\n\n${request.researchData}`,
      },
    ],
    temperature: 0.7,
    max_tokens: 3000,
  });

  return completion.choices[0].message.content || '';
}

4. Video Generation with Remotion

typescript

// src/lib/video/render-video.ts
import { bundle } from '@remotion/bundler';
import { renderMedia, selectComposition } from '@remotion/renderer';
import path from 'path';

interface VideoConfig {
  title: string;
  content: string;
  aspectRatio: '9:16' | '16:9' | '1:1'; // TikTok, YouTube, Instagram
}

export async function renderContentVideo(
  config: VideoConfig
): Promise<string> {
  const compositionId = 'ContentVideo';
  const bundleLocation = await bundle({
    entryPoint: path.resolve('./remotion/index.ts'),
    webpackOverride: (config) => config,
  });

  const composition = await selectComposition({
    serveUrl: bundleLocation,
    id: compositionId,
    inputProps: {
      title: config.title,
      content: config.content,
      aspectRatio: config.aspectRatio,
    },
  });

  const outputLocation = path.join(
    process.cwd(),
    'public',
    'videos',
    `${Date.now()}.mp4`
  );

  await renderMedia({
    composition,
    serveUrl: bundleLocation,
    codec: 'h264',
    outputLocation,
    inputProps: composition.props,
  });

  return outputLocation;
}

5. Complete Pipeline Implementation

typescript

// src/lib/pipeline/content-pipeline.ts
import { crawlTechNews } from '../crawlers/news-crawler';
import { generateContentWithClaude } from '../ai/claude-generator';
import { renderContentVideo } from '../video/render-video';

export interface PipelineConfig {
  keyword: string;
  format: 'toplist' | 'pov' | 'case-study' | 'how-to';
  language: 'en' | 'vi';
  tone: 'expert' | 'friendly' | 'humorous';
  generateVideo: boolean;
  videoAspectRatio?: '9:16' | '16:9' | '1:1';
}

export async function runContentPipeline(config: PipelineConfig) {
  console.log(`Starting pipeline for keyword: ${config.keyword}`);

  // Step 1: Research & Crawl
  console.log('Step 1: Crawling news sources...');
  const newsArticles = await crawlTechNews(config.keyword);
  const researchData = newsArticles
    .map(
      (article) =>
        `Title: ${article.title}\nURL: ${article.url}\nContent: ${article.content}\n---`
    )
    .join('\n\n');

  // Step 2: Generate Content
  console.log('Step 2: Generating content with AI...');
  const generatedContent = await generateContentWithClaude({
    keyword: config.keyword,
    format: config.format,
    language: config.language,
    tone: config.tone,
    researchData,
  });

  // Step 3: Render Video (if enabled)
  let videoPath: string | null = null;
  if (config.generateVideo) {
    console.log('Step 3: Rendering video...');
    videoPath = await renderContentVideo({
      title: config.keyword,
      content: generatedContent,
      aspectRatio: config.videoAspectRatio || '16:9',
    });
  }

  return {
    content: generatedContent,
    videoPath,
    sources: newsArticles,
    timestamp: new Date().toISOString(),
  };
}

Next.js API Route Example

typescript

// src/app/api/generate/route.ts
import { NextRequest, NextResponse } from 'next/server';
import { runContentPipeline } from '@/lib/pipeline/content-pipeline';

export async function POST(request: NextRequest) {
  try {
    const body = await request.json();
    
    const result = await runContentPipeline({
      keyword: body.keyword,
      format: body.format || 'toplist',
      language: body.language || 'en',
      tone: body.tone || 'expert',
      generateVideo: body.generateVideo || false,
      videoAspectRatio: body.videoAspectRatio || '16:9',
    });

    return NextResponse.json({
      success: true,
      data: result,
    });
  } catch (error) {
    console.error('Pipeline error:', error);
    return NextResponse.json(
      { success: false, error: 'Content generation failed' },
      { status: 500 }
    );
  }
}

Frontend Component Example

typescript

// src/components/ContentGenerator.tsx
'use client';

import { useState } from 'react';

export default function ContentGenerator() {
  const [keyword, setKeyword] = useState('');
  const [loading, setLoading] = useState(false);
  const [result, setResult] = useState<any>(null);

  const handleGenerate = async () => {
    setLoading(true);
    try {
      const response = await fetch('/api/generate', {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify({
          keyword,
          format: 'toplist',
          language: 'en',
          tone: 'expert',
          generateVideo: true,
          videoAspectRatio: '16:9',
        }),
      });

      const data = await response.json();
      setResult(data.data);
    } catch (error) {
      console.error('Generation failed:', error);
    } finally {
      setLoading(false);
    }
  };

  return (
    <div className="p-6">
      <input
        type="text"
        value={keyword}
        onChange={(e) => setKeyword(e.target.value)}
        placeholder="Enter keyword..."
        className="border p-2 rounded w-full"
      />
      <button
        onClick={handleGenerate}
        disabled={loading}
        className="mt-4 bg-blue-600 text-white px-6 py-2 rounded"
      >
        {loading ? 'Generating...' : 'Generate Content'}
      </button>

      {result && (
        <div className="mt-6">
          <h3 className="font-bold">Generated Content:</h3>
          <div className="prose">{result.content}</div>
          {result.videoPath && (
            <video src={result.videoPath} controls className="mt-4" />
          )}
        </div>
      )}
    </div>
  );
}

Remotion Video Template

typescript

// remotion/ContentVideo.tsx
import { AbsoluteFill, useCurrentFrame, interpolate } from 'remotion';

interface ContentVideoProps {
  title: string;
  content: string;
  aspectRatio: '9:16' | '16:9' | '1:1';
}

export const ContentVideo: React.FC<ContentVideoProps> = ({
  title,
  content,
}) => {
  const frame = useCurrentFrame();
  const opacity = interpolate(frame, [0, 30], [0, 1]);

  return (
    <AbsoluteFill
      style={{
        backgroundColor: '#000',
        justifyContent: 'center',
        alignItems: 'center',
      }}
    >
      <div style={{ opacity }}>
        <h1 style={{ color: '#fff', fontSize: '48px' }}>{title}</h1>
        <p style={{ color: '#fff', fontSize: '24px', marginTop: '20px' }}>
          {content.substring(0, 200)}...
        </p>
      </div>
    </AbsoluteFill>
  );
};

Common Patterns

Batch Content Generation

typescript

async function generateBatchContent(keywords: string[]) {
  const results = await Promise.all(
    keywords.map((keyword) =>
      runContentPipeline({
        keyword,
        format: 'toplist',
        language: 'en',
        tone: 'expert',
        generateVideo: false,
      })
    )
  );
  return results;
}

Scheduled Content Pipeline

typescript

// Use with cron or task scheduler
import cron from 'node-cron';

cron.schedule('0 9 * * *', async () => {
  // Run daily at 9 AM
  const trendingKeywords = ['AI', 'Web3', 'Marketing Automation'];
  await generateBatchContent(trendingKeywords);
});

Troubleshooting

API Rate Limits

typescript

// Implement rate limiting
import pLimit from 'p-limit';

const limit = pLimit(3); // Max 3 concurrent requests

const results = await Promise.all(
  keywords.map((keyword) =>
    limit(() => runContentPipeline({ keyword, /* ... */ }))
  )
);

Video Rendering Timeout

typescript

// Increase timeout in Remotion config
await renderMedia({
  composition,
  serveUrl: bundleLocation,
  codec: 'h264',
  outputLocation,
  timeoutInMilliseconds: 300000, // 5 minutes
});

Claude/OpenAI Error Handling

typescript

async function generateWithRetry(request: ContentRequest, maxRetries = 3) {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await generateContentWithClaude(request);
    } catch (error) {
      if (i === maxRetries - 1) throw error;
      await new Promise((resolve) => setTimeout(resolve, 1000 * (i + 1)));
    }
  }
}

Environment Variable Validation

typescript

// src/lib/utils/validate-env.ts
export function validateEnv() {
  const required = [
    'ANTHROPIC_API_KEY',
    'OPENAI_API_KEY',
    'RAPIDAPI_KEY',
  ];

  const missing = required.filter((key) => !process.env[key]);

  if (missing.length > 0) {
    throw new Error(`Missing environment variables: ${missing.join(', ')}`);
  }
}

marketing-pipeline-automation

NPX Install

Tags

SKILL.md Content

Marketing Pipeline Automation

What This Project Does

Installation

Prerequisites

Clone and Setup

Environment Configuration

Key Commands

Development

Remotion Video Rendering

Core Architecture

Project Structure

API Usage Patterns

1. Content Research & Crawling

2. AI Content Generation with Claude

3. OpenAI Alternative

4. Video Generation with Remotion

5. Complete Pipeline Implementation

Next.js API Route Example

Frontend Component Example

Remotion Video Template

Common Patterns

Batch Content Generation

Scheduled Content Pipeline

Troubleshooting

API Rate Limits

Video Rendering Timeout

Claude/OpenAI Error Handling

Environment Variable Validation