youtube-summarize

What This Skill Does

The youtube-summarize skill is a powerful tool designed to bridge the gap between long-form video content and concise text analysis. By leveraging the industry-standard yt-dlp library, this skill automates the extraction, cleaning, and formatting of YouTube transcripts and metadata. It enables users to bypass hours of video watching by programmatically fetching auto-generated or manual subtitles, removing technical artifacts like timestamps and VTT headers, and preparing the raw data for consumption by an LLM. Beyond just transcripts, the skill can extract granular metadata such as view counts, channel details, video descriptions, and even chapter markers, providing a holistic view of the video content.

Installation

To begin using this skill, ensure you have Python 3 installed on your machine. Install the prerequisite downloader by running pip install yt-dlp. Once the dependencies are met, you can install the skill via the OpenClaw agent platform using the command: clawhub install openclaw/skills/skills/sakaen736jih/yt-summarize.

Use Cases

This skill is ideal for researchers who need to synthesize information from various video lectures, content creators analyzing competitors' videos, or students aiming to summarize educational content. It is also excellent for accessibility, allowing users to quickly search through the textual content of a video for specific keywords or concepts.

Example Prompts

1. "Summarize the key takeaways from the video at [URL] and list them as bullet points."
2. "Can you extract the chapters from this YouTube video [URL] and provide a quick overview for each section?"
3. "Fetch the transcript for [URL] in Spanish and translate it into a concise summary."

Tips & Limitations

The accuracy of the summary is heavily dependent on the quality of the YouTube transcript; videos without captions or with poor auto-generated subtitles may yield lower-quality summaries. While the skill supports multi-language extraction, ensure that the video has the specific subtitle track available. For long videos, you may need to break the transcript into smaller chunks if the resulting text exceeds the context window of your connected AI model. Always verify critical facts against the original source when dealing with highly technical or academic material.