YouTube Chapters & Timestamps Generator
Pricing
from $50.00 / 1,000 video chapters generateds
YouTube Chapters & Timestamps Generator
Generate YouTube-ready chapter timestamps, an SEO video description and tags from any YouTube video's transcript. Paste video URLs, copy the chapters.
Pricing
from $50.00 / 1,000 video chapters generateds
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Developer
Seemu Scraping
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2 days ago
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Paste YouTube video URLs and get paste-ready chapter timestamps, an SEO-friendly video description and a set of tags for each one. Chapters are built from the video's transcript, so they land where the topic actually changes, and every list follows YouTube's chapter rules.
What you get
For every video:
- chaptersText - the chapter block, ready to paste into your YouTube description:
0:00 Why Docker solves the works on my machine problem1:37 Images and containers: Docker recipes and runnable instances2:54 Installing Docker and preparing your development environment3:37 Writing a Dockerfile for a Node.js server
- chapters - the same list as data: startSeconds, timestamp and title for each chapter
- seoDescription - a 120-250 word description with your main keyword in the first line
- descriptionWithChapters - the description with the chapter block appended, ready to paste in one go
- tags - 12-20 search tags, trimmed to fit YouTube's 500-character tag limit
- existingChapters and hasExistingChapters - the chapters the video already has, so you can compare
- Video details: videoId, url, title, channelName, durationSeconds, transcriptLanguage
- status and error for every row
YouTube chapter rules, handled for you
YouTube only shows chapters when the list follows its rules. Every list this tool returns:
- starts at 0:00
- has at least 3 chapters
- keeps every chapter at least 10 seconds long (30 seconds by default, you can change it)
- is in time order, with no duplicates and nothing past the end of the video
- uses
m:sstimestamps, orh:mm:ssfrom the one-hour mark
Timestamps are taken from the transcript line where each new topic starts, so clicking a chapter jumps to the right moment.
Use cases
- YouTube creators - add chapters to new uploads in seconds instead of scrubbing through the timeline
- Back-catalogue SEO - add chapters, descriptions and tags to hundreds of older videos so they show up as key moments in Google and YouTube search
- Podcasts and long interviews - chapter 2-3 hour episodes so viewers can jump to the guest or topic they want
- Agencies and editors - deliver chapters, descriptions and tags for client channels in bulk
- Course and tutorial makers - turn lessons into skimmable, step-by-step sections
How to use
- Enter one or more Video URLs (or video IDs), up to 50 per run.
- Pick a Chapter title style: Concise, Descriptive or Keyword-rich.
- Optionally change Minimum chapter length (default 30 seconds) and Maximum chapters (default 15).
- Leave Output language empty to match the video, or type a language such as
Spanishto translate the chapters, description and tags. - Run the tool. Results appear in the Dataset tab. Copy chaptersText (or descriptionWithChapters) straight into YouTube Studio.
Output example
{"inputUrl": "https://www.youtube.com/watch?v=8jPQjjsBbIc","videoId": "8jPQjjsBbIc","url": "https://www.youtube.com/watch?v=8jPQjjsBbIc","title": "How to stay calm when you know you'll be stressed | Daniel Levitin | TED","channelName": "TED","durationSeconds": 741,"hasExistingChapters": true,"existingChapters": [{ "startSeconds": 0, "timestamp": "0:00", "title": "The personal crisis" }],"chapters": [{ "startSeconds": 0, "timestamp": "0:00", "title": "Breaking into his own home and forgetting his passport" },{ "startSeconds": 192, "timestamp": "3:12", "title": "Using a premortem to anticipate what could go wrong" },{ "startSeconds": 236, "timestamp": "3:56", "title": "Building reliable places for everyday essentials" }],"chaptersText": "0:00 Breaking into his own home and forgetting his passport\n3:12 Using a premortem to anticipate what could go wrong\n3:56 Building reliable places for everyday essentials","seoDescription": "Stress management starts before the crisis: neuroscientist Daniel Levitin shows how a premortem can keep stress from clouding important decisions...","descriptionWithChapters": "Stress management starts before the crisis: ...\n\n0:00 Breaking into his own home and forgetting his passport\n3:12 ...","tags": ["stress management", "premortem", "prospective hindsight", "Daniel Levitin", "TED talk"],"chapterStyle": "descriptive","transcriptLanguage": "en","transcriptIsAutoGenerated": false,"transcriptTruncated": false,"model": "openai/gpt-6-luna","status": "success","error": null}
Pricing
Each video that gets chapters is charged a small base fee plus a per-minute fee for the length of the video, so a 5-minute clip costs a fraction of a 3-hour podcast. Videos without captions, private or removed videos, and videos too short for chapters are reported with an error and are not charged.
Tips
- Keyword-rich titles help chapters appear as "key moments" in Google search. Concise titles read best on mobile.
- For long podcasts, raise Minimum chapter length to 120-300 seconds to get fewer, bigger sections.
- A video must be at least 3 x the minimum chapter length long (90 seconds at the default). Lower the minimum to 10-20 seconds for short videos.
- If the video's captions are in a language you want to skip, list the languages to use under Transcript languages.
FAQ
Does it work on videos without captions? No. Chapters are built from the video's manual or auto-generated captions. Videos with captions turned off return a row with an error and are not charged.
Does it work on long videos? Yes. The default model reads the full transcript in one pass, so a 3-hour podcast gets chapters that cover the whole episode.
My video already has chapters. Why run it? The original chapters are returned in existingChapters so you can compare. Many creators use this to tighten vague chapter titles or add search keywords.
Can I get chapters in another language?
Yes. Set Output language to any language name, for example German. Chapter titles, description and tags are all written in that language.