What is read, what is sent, what is kept.
A verdict is a model's judgment of the video's captions, checked by code. Here is each step, and which parts are code and which are a model.
From the click to the verdict.
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The captions are read in your browser
The extension reads the caption track the video page already has, in your own session, the same way the player does. Our server never asks YouTube for a transcript.
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The text is sent, with the title
The caption segments go to our server over an encrypted connection, with the video id, title, channel, length, and caption language. A random install id or your session goes with them. Nothing else does.
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The transcript is cut into numbered blocks
Code groups the captions into 30-second blocks, each numbered and stamped with its start time. The model sees the blocks.
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The model judges
A call returns the verdict, the reason, the points, the start of the substance, the skip ranges, and the promise check. It cites block numbers, never times. A transcript too long for one call is judged in parts and merged by a last call.
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Code turns blocks into timestamps
Every block number becomes the start time of its first caption, so a timestamp always lands where the words are. The model never invents a time.
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The verdict is cached and shown
The verdict is kept by video id so the next person gets it free. The transcript is discarded unless you save the verdict on Pro.
Which parts are code and which are a model.
- Code
Reading the captions and cutting the blocks. Every timestamp. The no-captions and lyrics checks. The limits and the cache. The digest's feed reading and the email.
- The model
The verdict word and the reason. The points. Which block the substance starts in. The skip ranges and their labels. The promise check. The digest's one-line summary.
- Checked by code after the model
The answer must match a strict schema: the right words, the right counts, block numbers that exist. An answer that fails is asked for again, three tries in all. After that the panel says no verdict came back, never half a verdict.
Which model, and what it costs.
The reference model is Claude Haiku 5.5 with a strict output schema. Cheaper open models on Cloudflare Workers AI were scored against the same twelve test transcripts.
The model in use is named on this page: Claude Haiku 5.5, from Anthropic. When a call to Anthropic fails, the verdict comes from Qwen3 30B on Cloudflare Workers AI instead.
On the 12 test transcripts it matched the hand-written verdict on 9 of 12. It placed the start of the substance within one block on 9, and found 3 of the 3 sponsor ranges. The test set and the scoring script are in the open.
A verdict costs under a cent to produce. The transcript is never used to train a model.
What a verdict cannot do.
It reads words, not pictures. A video whose value is in what is shown rather than said can be misjudged.
Auto-generated captions misspell names and numbers. The panel says when the captions were auto-generated.
It judges against the title. A video with a modest title and rich content reads as "delivers" even when the content is thin for you.
It is a judgment. Two careful people would disagree on some verdicts, and so will you.
How the digest finds new videos.
Every channel has a public feed of its latest uploads. Once an hour, our server reads the feeds of channels at least one person follows.
For each new video it buys one transcript from a transcript provider and analyzes it once. The verdict is shared with every subscriber of that channel.
At your local 7 am the email goes out with the day's verdicts, Watch rows first. If nothing new came in, no email is sent.
What is kept, and for how long.
- Kept
Your email, your plan, your channels, and your digest settings. The verdicts you saved on Pro, with their transcripts. The shared verdict cache, which holds no personal data.
- Not kept
Transcripts you did not save, your questions to Ask the video and their answers, your YouTube account, your watch history, your cookies.
- Deleted on request
Everything tied to your account, from the account page, in one step.