Дела подождут, а вот мемчики сами себя не посмотрят. #трололошная открыта. Делитесь своими мемными запасами в комментариях, зовите друзей, коллег — будем хихикать все вместе.
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Channel
@zavtrak_s_Kilinoy
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry
62,639subscribers
-540 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001351111138 |
|---|---|
| Type | Channel |
| Username | @zavtrak_s_Kilinoy |
| Description | Канал об эффективности и продуктивности. Здесь говорим о том, как устроен наш мозг. Интересные исследования. Личный канал https://t.me/by_Kilina По вопросам рекламы: [email protected] https://knd.gov.ru/license?id=673a48566afad41667c331e9®istryType=b |
| Created | 14 March 2018 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 7 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 31 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/zavtrak_s_Kilinoy |
Health & wellness — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 96% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 08:17 | 62,639 | +15 |
| 15 Sept 2026, 04:41 | 62,624 | -29 |
| 13 Sept 2026, 13:58 | 62,653 | -18 |
| 11 Sept 2026, 17:36 | 62,671 | -49 |
| 9 Sept 2026, 02:01 | 62,720 | -55 |
| 5 Sept 2026, 14:59 | 62,775 | -17 |
| 3 Sept 2026, 14:18 | 62,792 | -23 |
| 2 Sept 2026, 05:27 | 62,815 | -13 |
| 1 Sept 2026, 07:08 | 62,828 | -9 |
| 31 Aug 2026, 05:13 | 62,837 | -14 |
| 30 Aug 2026, 05:13 | 62,851 | -4 |
| 29 Aug 2026, 02:15 | 62,855 | -12 |
| 28 Aug 2026, 02:47 | 62,867 | -25 |
| 26 Aug 2026, 23:49 | 62,892 | -9 |
| 25 Aug 2026, 22:16 | 62,901 | -17 |
| 24 Aug 2026, 23:59 | 62,918 | -33 |
| 23 Aug 2026, 08:02 | 62,951 | -4 |
| 21 Aug 2026, 18:57 | 62,955 | -7 |
| 20 Aug 2026, 15:52 | 62,962 | -33 |
| 19 Aug 2026, 14:28 | 62,995 | first reading |
64 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 102 pages of Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 24 September 2026 |
|---|---|
| Posts held | 64 (28 July 2026 – 24 September 2026) |
| Views total | 218,600 |
| Reactions total | 6,513 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 24 Sept 2026, 14:58 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.
Lifetime counters from Telegram’s own channel header, read 24 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Measured directly from 40 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
13,710 reactions across 64 posts, in 21 distinct kinds. The most used accounts for 64.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 8,862 | 64.6% | |
| 🔥 | 1,566 | 11.4% | |
| 😁 | 1,254 | 9.15% | |
| 👍 | 910 | 6.64% | |
| ❤🔥 | 687 | 5.01% | |
| custom 5343953413837189939 | 226 | 1.65% | |
| 🤩 | 49 | 0.357% | |
| 👏 | 43 | 0.314% | |
| 💘 | 28 | 0.204% | |
| 🤔 | 22 | 0.16% | |
| ⚡ | 19 | 0.139% | |
| ☃ | 13 | 0.095% | |
| 🌚 | 10 | 0.073% | |
| 🥰 | 9 | 0.066% | |
| 🎅 | 3 | 0.022% | |
| 🎉 | 2 | 0.015% | |
| 👎 | 2 | 0.015% | |
| 😱 | 2 | 0.015% | |
| 😍 | 1 | 0.007% | |
| 🙉 | 1 | 0.007% | |
| 1 further kind | 1 | 0.007% |
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 64 of the 64 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 13,710 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 64 most recent posts we hold, published 28 July 2026 to 24 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Дела подождут, а вот мемчики сами себя не посмотрят. #трололошная открыта. Делитесь своими мемными запасами в комментариях, зовите друзей, коллег — будем хихикать все вместе.
😁96❤🔥21❤10🤩4
1758. Свои настройки для отдыха #завтрак Мы часто слышим: «Устал — надо поспать». Но сон не универсальное решение. Усталость бывает разной, и для каждой нужен свой ключ. Сегодня будем разбираться, что нужно каждому из вас. Начнём разрабатывать ваш план по восстановлению. 💬 В комментариях делитесь, что из перечисленного хотите попробовать.
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1757. Почему после отдыха мы всё равно уставшие #завтрак Вчера говорили об усталости. Сегодня — об отдыхе. И тут важный момент: отдых не всегда равно восстановление. Можно лежать весь день и так и не вернуть силы. Учёные выделяют четыре модели восстановления. Если усталость не уходит — возможно, какой-то из них вам не хватает. Включайте эфир. Будем разбираться. 💬 В комментариях напишите, какая частичка у вас прос…
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1756. Что на самом деле вас выматывает #завтрак Мы часто спрашиваем себя: «Почему я так устал(а)?». Я предлагаю заменить этот вопрос на другой. В этой замене — ключ ко многому. Включайте эфир ▶️ Сегодня поговорим о том, какой вообще бывает усталость и что именно влияет на вас. Поднимаю эту тему, потому что скоро стартует Проект Икс. Там мы в том числе разбираем ресурсы, то, почему стоим на месте и что с этим дела…
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Понедельник ⏰ включайте секундомеры)) Сегодня в рубрике #пятьминутизвилинам будем искать числа от 1 до 48. В комментариях пишите, за сколько справились.
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1755. У меня есть возможность #завтрак На прошлой неделе я наткнулась на видео, которое до сих пор не выходит у меня из головы. В нем очень простой прием, но он прям меняет взгляд на привычные вещи. ▶️ Включайте видео, расскажу, что это за прием и почему он так действует. В комментариях делитесь своими «волшебными словами» — может, вы тоже как-то перепрограммируете себя в моменте.
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1754. Книги НЕТ #завтрак Случилось удивительное. Я полюбила художественную литературу и не успеваю читать нон-фикшн. Вернее, я выбрала не читать его. Сегодня у нас эфир-болталка ▶️ Поговорим о том, как так вышло, что у нас нет книжного обзора, и почему иногда стоит давать себе передышку — даже в том, что любишь. В комментариях пишите, что вы не выбираете осознанно.
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Четверг и лучшее время дня начинаются — #трололошная открыта 😹 Отправляйте свои мемчики в комментарии. И зовите друзей, будем хихикать вместе.
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1753. Парадоксы времени #завтрак Еще разик о том, как мы воспринимаем время. Сегодня подсоберем все самое интересное и парадоксальное. Один час может быть долгим и быстрым. Детство кажется огромным. Счастливые моменты пролетают как один миг. А минуты острого страха или шока тянутся бесконечно. И главный парадокс — время может не только замедляться или лететь, оно может ИСЧЕЗАТЬ. Когда мы живем на автопилоте, день…
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1752. Как эмоции растягивают время #завтрак В момент острого страха, шока время будто замедляется. Образы становятся ярче, звуки — резче, и кажется, что всё происходит как в замедленной съёмке. Сегодня поговорим о том, почему так бывает и как наши эмоции влияют на восприятие времени. 💬 В комментариях делитесь своим самым «медленным» моментом в жизни. Но если это был трагический случай, то лучше не пишите, чтобы не…
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1751. Куда уходит время и как его удержать #завтрак Мы все чувствуем время по-разному. Две минуты в планке тянутся как вечность, а когда такси уже приехало, а ты ещё не вышел — эти же две минуты пролетают мгновенно. Но что стоит за этим ощущением? Сегодня поговорим о том, как мы воспринимаем время с точки зрения психологии и как сделать так, чтобы жизнь не пролетала мимо. 💬 В комментариях делитесь своими лайфхакам…
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1750. Можно начинать прямо сейчас #завтрак Если вдруг вы задумываете начать новую жизнь – не обязательно ждать нового года. Понедельники тоже работают. Сегодня поговорим о временных вехах, эффекте нового старта и о том, как это использовать в свою пользу. 💬 В комментариях пишите, получалось ли у вас когда-нибудь провернуть что-нибудь такое.
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Showing the 12 most recent of 64 posts we hold for @zavtrak_s_Kilinoy. 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.
@zavtrak_s_Kilinoy edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 21 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 54 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“Завтрак с Килиной” (@zavtrak_s_Kilinoy), 62,639 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/zavtrak_s_Kilinoy.
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.