Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 44% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 1 of the 8 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 19 comparable posts for this entry, running 28 July 2026 to 6 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 2, the earliest publisher we hold is @bestpromptai. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
4 measurements spanning 3 days, net -29. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 5,212–5,249 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
10 Aug 2026, 12:35
5,216
-26
7 Aug 2026, 23:08
5,242
-3
7 Aug 2026, 16:01
5,245
no change
7 Aug 2026, 15:58
5,245
first reading
Engagement
20 posts held, back to 28 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 7 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
2.38%
avg views ÷ 5,216 subscribers
Avg views / post
124
20 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
20
of 20 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 6 August 2026
Posts held
20 (28 July 2026 – 6 August 2026)
Views total
2,483
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 04:37 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
541
Videos
210
Links
298
Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Промпт:
morning cozy bedroom with soft pink bedding with lots of pillows, large panoramic window overlooking turquoise ocean and blue sky with fluffy clouds, delicate white sheer curtains gently flowing, wicker table with a cup of cappuccino on it, bouquet of delicate pink roses, photorealistic, vibrant and deep colors, warm natural sunlight, detailed textures of fabric and woven wicker, peaceful and inviting atmos…
Стратегия прототипирования
Выберите правильную степень детализации и метод прототипирования для решения дизайнерской задачи.
Промпт:
---
name: prototype-strategy
description: Choose the right prototyping fidelity and method for the design question.
---
# Prototype Strategy
You are an expert in choosing prototyping approaches that efficiently answer design questions.
## What You Do
You help teams choose the right f…
Промпт:
A cute little cat is lying on its back, sleeping and rolling around on an old wooden bench. The sunlight is shining through the tree branches, warming its fluffy belly and creating beautiful shadows. In front of it are some blooming peaches. This photo was taken with a Canon EOS R5 camera using a macro lens with an aperture of f/2.8. --ar 2:3 --v 7
@promty1
Тестовые сценарии
Создавайте сценарии юзабилити-тестирования с задачами, критериями успеха и руководствами по наблюдению.
Промпт:
---
name: test-scenario
description: Write usability test scenarios with tasks, success criteria, and observation guides.
---
# Test Scenario
You are an expert in writing usability test scenarios that reveal genuine user behavior.
## What You Do
You write test scenarios with realistic t…
Промпт:
a woman sitting on the white sand of a beach in transparent flip-flops with flowers, by Miroslava Sviridova, roses and violets, close-up, made of glass, many bright buds on the flip-flops, promotional photo of the product - beach flip-flops, lower corner, outstanding image, tanned, graphic, advertisement for flip-flops
@promty1
Диаграмма пользовательского потока
Создавайте диаграммы пользовательского потока, показывающие пути, решения и ветвления.
Промпт:
---
name: user-flow-diagram
description: Create user flow diagrams showing paths, decisions, and branch logic.
---
# User Flow Diagram
You are an expert in creating clear user flow diagrams that map paths through a product.
## What You Do
You create flow diagrams showing how users move …
Спецификация каркасного макета
Определите макеты каркасных страниц с приоритетом контента, размещением компонентов и аннотациями.
Промпт:
---
name: wireframe-spec
description: Specify wireframe layouts with content priority, component placement, and annotation.
---
# Wireframe Spec
You are an expert in creating annotated wireframe specifications.
## What You Do
You specify wireframe layouts defining content priori…
Промпт:
A stone statue of a beautiful woman holding a live gray cat in her arms, surrounded by red roses, in a gothic park, with a texture of stone and fur, in the style of a surreal photograph in soft colors, an artistic photograph --ar 9:16
@promty1
Чек-лист QA для дизайна
Создавайте чек-листы QA для проверки точности реализации дизайна.
Промпт:
---
name: design-qa-checklist
description: Create QA checklists for verifying design implementation accuracy.
---
# Design QA Checklist
You are an expert in creating systematic QA checklists for verifying design implementation.
## What You Do
You create checklists that help designers systematically verify that impleme…
Промпт:
A tiny fairy with blonde hair and wings sits on a huge rose and drinks from her cup, surrounded by drops of water playing in the sun. The fairy is dressed in a soft pink dress that contrasts beautifully with the white petals of the flower. She has delicate facial features that convey every detail of her appearance, giving the impression that she is right there with you, drinking tea with us. This image conve…
Дизайн-критика
Организация структурированных критик дизайна с четкими рамками обратной связи и практическими результатами.
Промпт:
---
name: design-critique
description: Facilitate structured design critiques with clear feedback frameworks and actionable outcomes.
---
# Design Critique
You are an expert in facilitating productive design critiques that improve work and grow teams.
## What You Do
You structure and f…
Showing the 12 most recent of 20 posts we hold for @promty1. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 August 2026 — this
entry's latest reading, not the date you are reading this.
“ПРОМТЫ” (@promty1), 5,216 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/promty1.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.