How much does the transcription cost?

Using Gemini Flash, the cost is approximately $0.005 per hour of audio, making it an extremely affordable solution for high-volume transcription.

Does it support video formats other than YouTube?

This skill is specifically optimized for YouTube via the yt-dlp utility, which handles various YouTube URL formats and playlist structures.

What are the requirements for using YouTube Ingest?

You need a Gemini API key (GEMINI_API_KEY environment variable), yt-dlp installed on your system, and the Bun runtime to execute the ingestion scripts.

Where are the transcriptions saved?

By default, the skill outputs Markdown files to the 'output/youtube/' directory, including video metadata like title, channel, and source URL.

Can I process entire YouTube playlists at once?

Yes, you can use the --playlist flag to list or transcribe multiple videos from a playlist, with the option to limit the number of videos processed.

YouTube Ingest

Name: YouTube Ingest
Author: cdeistopened

bycdeistopened

•

Content Management

Transcribes YouTube videos and playlists into structured Markdown documents using Gemini Flash and yt-dlp.

YouTube Ingest is a specialized Claude Code skill that automates the conversion of video content into high-quality, searchable text. By utilizing yt-dlp for audio extraction and the cost-effective Gemini Flash model for transcription, it allows users to process single videos or entire playlists into polished Markdown files complete with metadata. This tool is essential for developers, researchers, and content creators looking to build local knowledge bases, summarize lectures, or archive technical insights from YouTube directly within their development workflow.

Key Features

01Configurable ingestion limits for large video series

02High-speed transcription using Gemini Flash

03Bulk processing support for full YouTube playlists

048 GitHub stars

05Structured Markdown output with YAML frontmatter

06Automated audio extraction via yt-dlp integration

Use Cases

01Converting video-based documentation into accessible text formats

02Extracting insights and summaries from long-form video interviews

03Building a searchable technical knowledge base from conference talks and tutorials

Key Features

01Configurable ingestion limits for large video series

02High-speed transcription using Gemini Flash

03Bulk processing support for full YouTube playlists

048 GitHub stars

05Structured Markdown output with YAML frontmatter

06Automated audio extraction via yt-dlp integration

Use Cases

01Converting video-based documentation into accessible text formats

02Extracting insights and summaries from long-form video interviews

03Building a searchable technical knowledge base from conference talks and tutorials