ScribeShot
Product documentation
Generate timestamped chapters for a YouTube video
Chapters turn a long recording into a navigable outline. ScribeShot generates topic sections from the transcript, resolves their timestamps back to the source text, and uses those sections throughout the note workspace.
Updated
Quick workflow
- 1
Add a video with an available transcript.
- 2
Generate chapters from the video workspace.
- 3
Scan the chapter list to understand the lesson before committing to a full watch.
- 4
Select a chapter to jump back to that point in the source video.
What a ScribeShot chapter represents
A chapter is a meaningful topic boundary rather than an arbitrary time slice. It carries a title or question, a source timestamp, and the key points needed to understand what that part of the lesson covers. Longer sections can also have structured subsections.
How timestamps are corrected
The language model proposes the structure, but ScribeShot does not blindly trust a generated timestamp. During generation it uses a quote from the source transcript to resolve the real point in the video, then enforces sensible ordering. This correction step is especially important when a long video is processed in multiple transcript chunks.
Use chapters as a focus tool
For a one-hour lecture, reading the chapter outline first answers two useful questions: what is actually in this video, and which sections deserve your attention? You can jump directly to a chapter, capture a visual, or use AI Video Highlights for a shorter first pass.
Chapters connect the rest of the workspace
The same topic structure supports AI notes, screenshot placement, mind-map navigation, and timestamped exports. That is why ScribeShot treats chapters as part of the lesson model rather than as a separate table of contents.
Common questions
Can I jump from a chapter back to the video?
Yes. Chapters are tied to source timestamps so they function as navigation points into the saved YouTube lesson.
Why are ScribeShot timestamps more reliable than raw model output?
The app corrects generated chapter positions against matching text in the actual transcript instead of treating the model-proposed second as authoritative.
Try the workflow
Use it on a real YouTube video
Try three videos free, with three screenshots per video. No account or credit card is required.