No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by drpwchen · Claude Skill · ★ 100
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lecture-to-notes safe to install? View the security audit →
lecture-to-notes English · 繁體中文 Turn a lecture or conference recording into structured, slide-illustrated notes — and into a synced HTML viewer where the video, the timestamped transcript, and the curated summary sit on one page: the video highlights the matching note as it plays, and clicking any note timestamp seeks the video. Every expensive stage runs locally: Whisper ASR on your GPU, frame extraction, OCR, and a local vision model for slide semantics. An LLM is used only at the end, to write prose from evidence the pipeline already assembled. The design goal is not "summarize a video". It is traceability: every claim in the finished note should be attachable to a moment in the transcript and to the slide that was on screen at that moment. Most of the machinery here exists to make that link trustworthy rather than plausible. Why this exists Rehabilitation-medicine courses are notoriously hard to take notes on. Manual therapy, ultrasound scanning — the knowledge is in the motion, so at every course you see a forest of tripods: everyone records everything, planning to rewatch over dinner. Nobody actually rewatches hours of video
| Stars | 100 |
| Forks | 24 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 65.4536219028815/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-01 |
| Created | 2026-08-02 |
| Platforms | claude-code, cli, python |
| Est. Tokens | ~17k |
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lecture-to-notes is Lecture recordings → structured grounded notes + a synced HTML viewer: video, timestamped transcript and curated summary on one page. Local GPU pipeline (Whisper ASR · slide extraction · OCR · VLM sig. It is categorized as a Claude Skill with 100 GitHub stars.
lecture-to-notes is primarily written in Python. It covers topics such as claude-code, faster-whisper, lecture-notes.
You can find installation instructions and usage details in the lecture-to-notes GitHub repository at github.com/drpwchen/lecture-to-notes. The project has 100 stars and 24 forks, indicating an active community.
lecture-to-notes is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to lecture-to-notes on Agent Skills Hub include mcp-video-analyzer, youtube-to-knowledge, agent-second-brain. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: