Yt Transcript

What This Skill Does

The Yt Transcript skill by alti-systems is a powerful utility designed to bridge the gap between long-form video content and text-based analysis. It provides an automated pipeline for extracting high-quality, readable transcripts directly from YouTube videos. The engine employs a sophisticated dual-method approach: it first queries the high-speed Supadata API for clean, formatted text, and if that is unavailable, it gracefully falls back to the robust yt-dlp library to ensure you never walk away empty-handed. This tool is essential for users who need to process large amounts of video data without the time sink of manual viewing.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/alti-systems/yt-transcript

Ensure that you have your SUPADATA_API_KEY correctly configured in your .env file to leverage the primary API-based extraction method. If the API key is omitted, the skill will rely solely on the fallback yt-dlp method.

Use Cases

• Rapid Summarization: Generate text summaries of lengthy podcasts or lectures in seconds.
• Research & Fact Checking: Search specific keywords or citations within video transcripts for academic or professional research.
• Content Repurposing: Convert spoken YouTube content into blog posts, newsletters, or social media threads.
• Accessibility Enhancement: Quickly generate searchable text versions of video content for archival purposes.
• Educational Workflow: Extract specific instructional steps from "how-to" videos to save time during project execution.

Example Prompts

1. "/root/clawd/yt-transcript https://www.youtube.com/watch?v=dQw4w9WgXcQ. Please summarize the key takeaways and list the three most important points discussed in the video."
2. "Extract the transcript for video ID zPZ479g4B8I and identify if the speaker mentions the impact of AI on software engineering."
3. "Run the yt-transcript skill on this video and then provide a list of every tool mentioned by the host in the transcript."

Tips & Limitations

• Tip: If a video is particularly long, ensure your context window is sufficiently large if you intend to send the resulting transcript directly into an LLM for analysis.
• Tip: Use the direct video ID if the full URL causes parsing issues, as the tool handles IDs with higher reliability.
• Limitation: The quality of the transcript is dependent on the original video's audio clarity and the accuracy of YouTube's internal captioning systems. Extremely low-audio quality or heavy background noise may result in suboptimal transcription accuracy.