autoclipper

🥈Silver

AI-powered Auto-Clipper: automatically detects highlight segments from YouTube channels, Twitch/Kick live streams (via audience-retention data, chat spikes and timestamped comments), clips them with FFmpeg, generates subtitles using Whisper, and uploads them to a target YouTube channel. Includes a FastAPI + Celery backend, React + Tailwind frontend

1700Updated 3d ago

Intermediate30min to implementautomation

Saves ~120 min per use

Quick InstallView Source

git clone https://github.com/VadlapatiKarthik/autoclipper.git

Works with:

Claude

Overview

About This Skill

The Auto-Clipper skill is an advanced AI-powered tool designed to streamline the process of creating highlight segments from various video platforms, including YouTube channels and Twitch/Kick live streams. By leveraging audience-retention data, chat spikes, and timestamped comments, this skill automatically detects the most engaging moments and clips them using FFmpeg. Additionally, it generates subtitles with Whisper and uploads the final clips to a designated YouTube channel, making it an invaluable asset for content creators and marketers looking to enhance their video offerings. One of the key benefits of the Auto-Clipper skill is its ability to save significant time for users. Instead of manually sifting through hours of footage to find the best moments, users can rely on this automation to handle the heavy lifting in just around 30 minutes of implementation. This efficiency allows developers, product managers, and AI practitioners to focus on more strategic tasks, such as content strategy and audience engagement, rather than getting bogged down in the minutiae of video editing. This skill is particularly useful for content creators, social media managers, and marketing teams who regularly produce video content and need to optimize their workflow. By automating the clipping process, these professionals can quickly generate shareable highlights that resonate with their audience, driving engagement and increasing viewership. For instance, a Twitch streamer can use Auto-Clipper to create highlight reels from their live sessions, which can then be shared across social media platforms to attract new followers. The implementation of the Auto-Clipper skill is rated as intermediate, requiring a basic understanding of FastAPI, Celery, and React with Tailwind for the frontend. This skill fits seamlessly into AI-first workflows by automating repetitive tasks, allowing teams to leverage AI automation for enhanced productivity. As organizations continue to embrace AI technologies, the Auto-Clipper skill stands out as a practical solution for anyone looking to optimize their video content creation process.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/VadlapatiKarthik/autoclipper

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I need to set up an Auto-Clipper for my [COMPANY] to automatically clip highlights from our [INDUSTRY] content on YouTube and Twitch. The system should detect segments based on audience retention data, chat spikes, and timestamped comments. It should then generate subtitles using Whisper and upload the clips to our target YouTube channel. Can you guide me through the setup process?

Example Output

# Auto-Clipper Setup Guide for [COMPANY]

## Step 1: Backend Setup
- **FastAPI + Celery Backend**: Clone the Auto-Clipper repository from GitHub.
- **Dependencies**: Install FFmpeg, Whisper, and other dependencies using the provided requirements.txt file.
- **Configuration**: Set up environment variables for YouTube API credentials, Twitch API credentials, and other necessary configurations.

## Step 2: Frontend Setup
- **React + Tailwind Frontend**: Navigate to the frontend directory and install dependencies using npm install.
- **Configuration**: Update the frontend configuration to point to your backend API endpoints.
- **Run the Frontend**: Start the development server using npm start.

## Step 3: Integration and Testing
- **YouTube and Twitch Integration**: Ensure your YouTube and Twitch channels are properly linked and authenticated.
- **Test Clipping**: Run a test clip to verify that the system correctly detects highlights, generates subtitles, and uploads the clip to your target YouTube channel.

## Step 4: Deployment
- **Backend Deployment**: Deploy the FastAPI + Celery backend to a cloud service like AWS, Google Cloud, or Azure.
- **Frontend Deployment**: Deploy the React + Tailwind frontend to a service like Vercel, Netlify, or AWS Amplify.
- **Monitoring**: Set up monitoring and logging to track the performance and reliability of the Auto-Clipper system.