youtube-extract-transcript

To extract a YouTube transcript automatically, this Skill uses the YouTube Data API for direct retrieval and applies intelligent cleaning to fix auto-generated errors, remove noise, and preserve timestamps. It handles rate limiting and provides context-aware corrections for accurate text output.

When standard YouTube captions are unavailable, extracting transcripts requires fallback methods like Whisper for audio transcription or EasyOCR for on-screen text. This Skill integrates these tools to ensure you can retrieve video text even without native subtitle tracks.

Yes, you need a YouTube Data API key for the full transcript extraction workflow. The Skill uses this key for direct API calls to retrieve captions and requires environment configuration via python-dotenv to manage your credentials securely.

OCR extracts on-screen text from YouTube videos by analyzing video frames using EasyOCR and OpenCV. This Skill leverages OCR as a fallback mechanism to capture visible text overlays when audio transcription or direct caption APIs are insufficient.

YouTube transcript extraction can fail due to API rate limiting or missing caption tracks. This Skill handles rate limiting with error fallbacks, automatically switching to Whisper or OCR methods to ensure continuous text extraction without interruptions.

Yes, you can use Whisper to transcribe YouTube audio as a fallback. When the direct YouTube transcript API fails or lacks captions, this Skill utilizes yt-dlp to download the video and OpenAI Whisper to generate an accurate transcript from the audio track.