Agent skill · marketing growth · aradotso
marketing-pipeline-ai-content-automation
Automate end-to-end content creation from research to video generation using AI (Claude/OpenAI) and Remotion
Why this skill is useful
Adds a complete executable content automation pipeline with AI integration and video rendering capabilities that the AI cannot generate on its own.
What it needs
Requires node, npm installed locally. Requires anthropic, openai, rapidapi account access. About 6k tokens when loaded. Last updated 2026-08-05. 8 stars on the source repository.
What this skill does
Marketing Pipeline AI Content Automation Skill by ara.so — Marketing Skills collection. Overview Marketing Pipeline is a comprehensive TypeScript-based content automation system that creates a complete content production pipeline. It automatically: 1. Research - Scrapes and analyzes real-time data from sources like TechCrunch, a16z, Twitter, and LinkedIn 2. Content Generation - Uses Claude 3 and OpenAI to create content in multiple formats (Top lists, POV, Case Studies, How-to) 3. Multi-language Output - Generates content in both English and Vietnamese with customizable tone 4. Video Rendering - Automatically converts content to videos and infographics using Remotion Installation Prerequisites Setup Environment Configuration Create a .env file with the following variables: Key Architecture Project Structure Core Workflows 1. Research & Data Collection Scraping Recent Content Custom Source Configuration 2. AI Content Generation Using Claude for Content Creation OpenAI Integration Multi-language Generation 3. Video Generation with Remotion Basic Video Rendering Custom Video Template Platform-Specific Export 4. Complete Pipeline Automation API Reference ResearchEngine ClaudeContentGenerator ContentPipeline Common Patterns Pattern 1: Daily Content Automation Pattern 2: Multi-Topic Content Generation Pattern 3: Custom AI Prompt Engineering Troubleshooting Issue: API Rate Limits Issue: Video Rendering Memory Issues Issue: Scraping Failures Issue: Content Quality Validation CLI Usage If the project includes CLI commands: Best Practices 1. Always use environment variables for API keys 2. Implement rate limiting when scraping external sources 3. Cache research data to avoid redundant API calls 4. Validate content quality before rendering videos 5. Use concurrency limits for video rendering to manage resources 6. Set up error monitoring for production pipelines 7. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/marketing-pipeline-ai-content-automation