youtube-clipper

Automate YouTube video clipping with AI-driven chapters and bilingual subtitles.

202|36|Updated Jan 27, 2026
One-click install
npx skills add https://github.com/adoresever/AGI_Ananas --skill youtube-clipper-adoresever
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: youtube-clipper
Source: https://github.com/adoresever/AGI_Ananas/tree/main/26.2.06OpenClaw%E6%A3%80%E7%B4%A2%E3%80%81%E5%AE%A1%E6%9F%A5%E6%89%A7%E8%A1%8C%E4%B8%8E%E5%A4%87%E4%BB%BDSkills/Youtube-clipper-skill
Command: npx skills add https://github.com/adoresever/AGI_Ananas --skill youtube-clipper-adoresever

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires yt-dlp, pysrt, python-dotenv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill automates the end-to-end YouTube video clipping workflow, generating AI-driven semantic chapters, clipping segments, translating subtitles, burning bilingual subtitles, and producing social-ready summaries.

Core Features & Use Cases

  • AI-driven semantic chapter analysis to create 2-5 minute segments aligned with content.
  • Deterministic clipping and bilingual subtitle generation for short-form content.
  • Social-media content generation and ready-to-publish outputs.

Quick Start

Clip a YouTube video by generating AI-driven chapters, extracting 2-minute clips with bilingual subtitles, and creating a summary for social platforms.

Frequently Asked Questions about youtube-clipper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate YouTube video clipping with AI-generated chapters?

Automating YouTube video clipping uses AI to analyze content and segment videos into 2-5 minute semantic chapters. This workflow extracts ready-to-share clips with bilingual subtitles and social media summaries.

How does AI semantic chapter analysis work for video segmentation?

AI semantic chapter analysis processes YouTube video content to identify topic boundaries and create 2-5 minute aligned segments. This mechanism replaces manual timestamping with deterministic clip extraction.

Do I need yt-dlp and pysrt to generate bilingual subtitles for clips?

Yes, you need yt-dlp, pysrt, and python-dotenv to generate bilingual subtitles. These dependencies coordinate environment checks, subtitle translation, and subtitle burning into the final clipped video output.

What is the best way to create social-ready clips from YouTube videos?

Creating social-ready clips involves AI-driven chapter segmentation, deterministic clipping, and bilingual subtitle generation. This approach produces ready-to-publish outputs with social media content summaries.

Can I burn translated subtitles directly into YouTube video clips?

Yes, you can burn translated subtitles directly into YouTube video clips. The workflow coordinates subtitle translation and burning to produce video segments with embedded bilingual subtitles.

What are the limitations of AI-driven YouTube clipping for short-form content?

AI-driven YouTube clipping limits segments to 2-5 minute semantic chapters optimized for short-form content. Users requiring arbitrary custom timestamps or non-YouTube sources may find the deterministic clipping restrictive.