Agent skill · marketing growth · aradotso
marketing-pipeline-share-ai-content
Automated content creation pipeline with AI research, multi-format writing, and video generation using Claude/OpenAI and Remotion
Why this skill is useful
Adds a complete automated content creation pipeline with executable scripts for AI research, multi-format writing, and video generation that the AI cannot generate on its own.
What it needs
Requires git, npm installed locally. Requires anthropic, openai, rapidapi account access. About 7k tokens when loaded. Last updated 2026-08-05. 8 stars on the source repository.
What this skill does
Marketing Pipeline Share - AI Content Automation Skill by ara.so — Marketing Skills collection. This skill enables AI coding agents to work with the Ultimate AI Content Pipeline - a comprehensive TypeScript-based system that automates the entire content creation workflow from research and scriptwriting to video generation and publishing. What It Does The Marketing Pipeline Share project provides: Auto-Research: Crawls and analyzes real-time data from TechCrunch, a16z, Twitter/X, LinkedIn AI Content Generation: Creates multi-format content (blog posts, case studies, how-tos) using Claude 3 and OpenAI Multi-Language Support: Generates content in both English and Vietnamese Video Generation: Automatically renders videos and infographics using Remotion Platform Optimization: Exports content optimized for Reels, TikTok, Shorts Installation Configuration Create a .env.local file in the root directory with required API keys: Project Structure Core API Usage 1. Research & Data Scraping 2. AI Content Generation with Claude 3. OpenAI Integration Alternative 4. Multi-Language Content Generation 5. Video Generation with Remotion 6. Complete Pipeline Workflow Next.js API Routes Content Generation Endpoint Video Rendering Endpoint Running the Application Common Patterns Pattern 1: Batch Content Generation Pattern 2: Content Scheduling Pattern 3: Custom Format Templates Troubleshooting API Rate Limits Video Rendering Memory Issues Content Quality Validation Environment Variables Reference Best Practices 1. Always validate input: Check keywords and parameters before processing 2. Implement rate limiting: Respect API limits for Claude/OpenAI 3. Cache research data: Avoid redundant scraping within 24h 4. Monitor costs: Track API usage for budget control 5. Test video renders: Verify output before batch generation 6. Use environment variables: Never hardcode API keys 7. Handle errors gracefully: Implement retry logic and fallbacks 8. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/marketing-pipeline-share-ai-content