
marketing-pipeline-share-content-automation
AI-powered content pipeline that auto-researches, generates scripts, and creates videos with Claude/OpenAI and Remotion
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/reason-machines/marketing-skills --skill marketing-pipeline-share-content-automation- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads marketing-pipeline-share-content-automation automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
- Cache research data to avoid redundant API calls
- Use queue systems (Bull, BullMQ) for video rendering
- Implement webhooks for async video completion notifications
- Store generated content in database for reuse
- Monitor API usage to stay within rate limits
- 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.
FAQ
What does the marketing-pipeline-share-content-automation skill do?
AI-powered content pipeline that auto-researches, generates scripts, and creates videos with Claude/OpenAI and Remotion
How do I install marketing-pipeline-share-content-automation?
Run npx skills add https://github.com/reason-machines/marketing-skills --skill marketing-pipeline-share-content-automation in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/marketing-pipeline-share-content-automation/ (personal) or .claude/skills/marketing-pipeline-share-content-automation/ (project).
Which AI agents can use marketing-pipeline-share-content-automation?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is marketing-pipeline-share-content-automation safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains marketing-pipeline-share-content-automation?
It is published by reason-machines in reason-machines/marketing-skills. It has 727 recorded installs.
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