A professional tool for extracting core structural insights, key arguments, and actionable steps from YouTube lecture transcripts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install youtube-lecture-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install youtube-lecture-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is YouTube Lecture Transcript Analyzer?
The YouTube Lecture Transcript Analyzer is a specialized utility designed to bridge the gap between long-form video content and structured knowledge management. By utilizing Openclaw Skills, this tool processes raw transcripts to identify the underlying structure of a lecture, distilling complex information into facts, claims, and actionable recommendations. It is specifically built for researchers, students, and technical writers who require high-fidelity summaries that maintain a direct link to the original source text.
The system focuses on high-integrity data extraction, ensuring that all synthesized points are backed by original quotes. It automatically cleanses transcripts of verbal fillers and errors, providing a polished and professional output that is ready for review or integration into larger projects. This makes it one of the most reliable Openclaw Skills for educational content processing.
YouTube Lecture Transcript Analyzer Use Cases
- Reviewing academic or technical seminars to quickly identify core arguments and supporting evidence.
- Generating structured study guides or meeting minutes from recorded video presentations.
- Creating high-quality blog posts or technical articles based on expert talks.
- Identifying actionable steps and highlight reels from long-form educational workshops.
How YouTube Lecture Transcript Analyzer Works
- Retrieve the video transcript using the YouTube URL or video ID via the integrated API.
- Clean the raw data by merging redundant points and removing speech-induced errors or verbal fillers.
- Map the lecture flow into 3 to 6 logical segments to create a structural overview.
- Categorize statements into specific types: Fact, Claim, Inference, or Recommendation.
- Extract specific 10-30 word quotes to serve as evidence for every key conclusion.
- Generate a dual-language summary and a comprehensive action checklist for the user.
YouTube Lecture Transcript Analyzer Setup
To use this skill, ensure you have the required dependencies installed and your network environment configured:
# Install the necessary library
pip install youtube-transcript-api
# Basic usage to analyze a video
python scripts/analyze_lecture.py <YouTube_URL>
# Analyze with specific language priority
python scripts/analyze_lecture.py <YouTube_URL> "zh-cn,en"
Note: This skill requires a local HTTP proxy running at 127.0.0.1:26739 for transcript fetching in certain regions.
YouTube Lecture Transcript Analyzer Data Schema & Taxonomy
The skill organizes its analysis into a strictly defined Markdown structure to ensure clarity and professional use:
| Section | Content Details |
|---|---|
| Core Summary | A single-sentence summary limited to 25 words. |
| Structure Map | 3-6 segments defining the lecture's progression. |
| Q&A Analysis | 5 critical questions identified and answered from the transcript. |
| Concept Map | Core concepts and the relationships between them. |
| Action Plan | A list of executable tasks derived from the lecture. |
| Highlights | Counter-intuitive points and key insights. |
| Verification | Blind spots or areas that require further fact-checking. |
| Dual Summary | 200-word summaries in both Chinese and English. |
YouTube Lecture Transcript Analyzer Advanced Features
- Evidence-linked extraction ensuring every point is cross-referenced with transcript quotes.
- Intelligent noise reduction to filter out verbal tics and redundant conversational filler.
- Multi-language priority settings to fetch the most relevant transcript version.
- Summary-only mode for rapid scanning of high-volume video lists.
- Semantic classification of content into Facts, Claims, Inferences, and Recommendations.
SKILL.md
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