Getting the transcript
Reading the captions from YouTube. A video nobody has opened here before takes 10 to 30 seconds; this page fills in on its own.
Getting the transcript
Reading the captions from YouTube. A video nobody has opened here before takes 10 to 30 seconds; this page fills in on its own.

Neural Stack Β· @neuralstack-p5d
Words
212
Runtime
1:00
Speaking pace
212wpm
Reading time
1min
212 words per minute, above the 201 75th percentile of 349 measured videos. That distribution comes from the 349-video hook study.
Opening (first 30 seconds)
Hey, Jarvis. Wake up. >> Welcome home, sir. >> [music] >> Congratulations on the new client for your SaaS app. >> I'm going to show you how to get this on your computer for free, and the whole thing is open source, so you can read the code, change it, and make it yours. Before anything works, you need VS Code or Cursor and Python. Grab the project from GitHub, click code, download zip, extract it, and you'll see all the files you need for the project to work. It's open source, so anyone can fork it and tweak it. Open VS Code or Cursor, click
106 words, the words spoken in the first 30 seconds at 212 words per minute.
Free, no signup. See how the first 30 seconds hold attention, with rewrites.
Sentence shape
| Measure | This transcript |
|---|---|
| Sentences | 20 |
| Average words per sentence | 10.6 |
| Longest sentence | 34 words |
| Questions asked | 0 |
| Sentences containing a number | 0 |
Most used terms
Filler phrases
1 in total: like 1.
A literal whole-word count of the same phrase list the Prepublish browser extension uses, so a phrase inside another word is not counted and a phrase used in its ordinary sense still is. It is a count and not a judgement.
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This transcript is under 300 words, so the page is marked noindex and does not appear in search results. The words stay here to read and to copy.
What this transcript is
Every word below is the caption track YouTube publishes for this video, pulled from the video itself and reproduced unchanged. It is not Prepublish's writing, not a summary, and not a re-transcription: it is the video's own published captions. English captions, generated automatically by YouTube, in the videoβs original language. Source: the video on YouTube. A channel that would rather this page did not exist can ask for its removal through the contact page, and it is removed.
No Script X-ray for this video: YouTube shows a Most replayed graph only once a video has enough views.
Hey, Jarvis. Wake up. >> Welcome home, sir. >> [music] >> Congratulations on the new client for your SaaS app. >> I'm going to show you how to get this on your computer for free, and the whole thing is open source, so you can read the code, change it, and make it yours. Before anything works, you need VS Code or Cursor and Python. Grab the project from GitHub, click code, download zip, extract it, and you'll see all the files you need for the project to work.
It's open source, so anyone can fork it and tweak it. Open VS Code or Cursor, click the open folder button, and pick the folder you just extracted. Open the terminal and run this install command. This pulls everything you need for the project to run. For the Jarvis voice, you need ElevenLabs. Create an API key, pick a voice, and copy the voice ID. Create a .env file in the same folder as Jarvis.py. Paste your key, your voice ID, and save it.
Run python Jarvis.py, and you should see it listening for claps. Clap twice quick, like this. If Spotify, Chrome, The Voice, and Cursor all fire, you're good. And that's how you get Jarvis on your computer. Want the full
The words are the caption track's own and nothing is reworded or re-transcribed. Paragraph breaks are placed between sentences so the text reads as prose.
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