Mirror — продукт на стыке mental health tech и AI, ориентированный на русскоязычную аудиторию.
https://t.me/mirror_y_bot - Мини-Апп
https://t.me/MirrorYapp/14 - APK на Android
https://mirror-y.web.app/ - Веб-приложение (сайт)
Created
Between 1 November 2025 and 26 December 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
2 measurements taken within a single day. 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 936–938 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Aug 2026, 00:50
937
no change
7 Aug 2026, 18:04
937
first reading
Engagement
20 posts held, back to 26 December 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 7 January 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Photos
25
Videos
9
Links
41
Lifetime counters from Telegram’s own channel header, read 8 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.
Video runtime
8m 50s
Average length
1m 06s
Measured directly from 8 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.
Reaction mix
325 reactions across 19 posts, in 4 distinct kinds. The most used accounts for 34.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
113
34.8%
🔥
97
29.8%
💯
90
27.7%
🕊
25
7.69%
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 19 of the 20 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 325reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 26 December 2025 to 7 January 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.
Telegram Stars
Stars received
5
across the posts below
Posts paid on
2
of 20 we hold a reading for · 10%
Most on one post
3
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @MirrorYapp. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 20 most recent posts we hold for this entry, published 26 December 2025 to 7 January 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Флоу Mirror: ввод → мини-диалог → анализ → результат → рефлексия → упражнение/дневник
Как работает Mirror? Всё очень просто:
1) Ввод
Вы описываете ситуацию. Что думаете, что чувствуете, что происходит. Это занимает минуту.
2) Мини-диалог
Mirror задаёт уточняющие вопросы. Не "расскажите всё", а конкретные вопросы, которые помогают глубже понять ситуацию.
3) Анализ
Mirror анализирует через ИИ. Находит паттерны, опр…
Когнитивные искажения: топ-5 ловушек (перфекционизм, катастрофизация, ч/б мышление, долженствование, чтение мыслей)
Ваш мозг упрощает реальность, чтобы быстрее принимать решения. Но иногда это создаёт искажения. Вот топ-5 ловушек:
1) Перфекционизм
"Я должен делать всё идеально" — это не про качество, а про страх ошибки. И этот страх парализует.
2) Катастрофизация
"Всё пойдёт не так" — это не про реализм, а про стр…
Почему мы не видим свои мысли со стороны: метафора "зеркала" + 3 примера самообмана
Почему мы не видим свои мысли со стороны? Потому что мы в них живём.
Вот метафора:
вы смотрите в зеркало и видите себя со стороны. Но с мыслями так не работает — вы не можете посмотреть на них со стороны, потому что вы в них живёте.
И это создаёт самообман. Вот 3 примера:
1) Перфекционизм
Вы думаете: "Я должен делать всё идеально"…
Mirror за 60 секунд: что это за Mini App в Telegram и чем отличается от "советов из интернета"
Вы знаете, что такое Mirror? Это Mini App в Telegram, которое помогает понять себя через ИИ.
Но чем оно отличается от обычных советов в интернете?
1) Персонализация
Не "вот 10 способов справиться с тревогой", а "вот анализ вашей тревоги, вот ваши паттерны, вот практики, которые подходят именно вам".
2) Анализ через ИИ
Н…
Связи и корреляции в Mirror: как находить "что на что влияет"
В Mirror всё связано. Сон влияет на мышление. Еда влияет на эмоции. Зависимости влияют на сон. И наоборот.
Mirror находит эти связи:
1) Сон ↔️ Мышление
"После плохого сна (менее 6 часов) когнитивные искажения растут на 20-30%" или "Качественный сон → больше ясности мышления".
2) Еда ↔️ Эмоции
"После нездоровой еды вы чаще тревожитесь" или "После качеств…
Жизненная лента и календарь в Mirror: зачем видеть жизнь "по дням"
В Mirror есть два способа смотреть на вашу жизнь:
1) Лента (хронология)
Все записи подряд: анализы, практики, сон, еда, зависимости. Как Instagram, но про ваше состояние.
2) Календарь
Визуализация по дням: какие дни были "лёгкими", какие "тяжёлыми", какие паттерны повторяются.
Зачем это нужно:
Вы видите не "хаос", а структуру
Не "у меня всегда плох…
Дневник паттернов в Mirror: как появляется статистика и "карта повторов"
Вы делаете анализ в Mirror. Сохраняете в дневник. Через неделю открываете - и видите статистику.
Не "кажется, я всегда тревожный". А конкретные данные:
- "За неделю вы сделали 7 анализов"
- "Самый частый паттерн - перфекционизм (35% случаев)"
- "Чаще всего тревога появляется вечером (после 20:00)"
- "После качественного сна паттернов на 20% ме…
Новое в Mirror: База знаний
Знаете, почему мы иногда думаем не так, как нужно? Почему одна мысль может испортить весь день?
В Mirror появилась База знаний. Первая тема - Когнитивные искажения.
Что это такое? Это 10 способов, как наш мозг обманывает нас каждый день:
🔹 Всё или ничего - видим только крайности
🔹 Катастрофизация - сразу думаем о худшем
🔹 Чтение мыслей - уверены, что знаем, что думают другие
🔹 Пророчес…
🧠 Вы едите не от голода. Вы едите от эмоций. И это нормально. Главное — это заметить.
Проверьте себя:
Когда вы в последний раз ели — не потому что хотели есть…
А потому что было тревожно? Скучно? Грустно? Стресс?
Вы не слабы. Вы не безвольны.
Вы просто не видите связи.
Эмоциональное питание — не про еду.
Это про то, как мы реагируем на внутреннее состояние.
Раньше я ел на автомате. Потом винил себя.
Пока не начал…
Зависимости без морализаторства в Mirror: кофеин/никотин/алкоголь/сахар как данные, а не "стыд"
Кофе, сигареты, алкоголь, сладкое - это не "плохо" или "хорошо". Это данные о вашем состоянии.
Mirror работает с зависимостями без морализаторства:
1) Вы фиксируете факт
"Выпил 3 чашки кофе", "Выкурил 5 сигарет", "Съел шоколадку" - просто записали, без оценки.
2) Mirror анализирует влияние
"Кофеин после 18:00 → плохой с…
🧠 Перфекционизм - это не стремление к идеалу. Это страх быть недостаточно хорошим.
Вы не ленивы.
Вы не медлительны.
Вы боитесь ошибиться.
Запускаете проект - и замираете.
Заканчиваете задачу - и снова переделываете.
Потому что «недостаточно хорошо» = «недостаточно достоин».
Я тоже думал: это моя сила.
На самом деле - это моя ловушка.
Пока не начал использовать Mirror - веб-приложение в Telegram, которое анализиру…
🧱 Giveaway Finished 🧱
Total tickets: 43969
Winners list:
1. Lol Pop #396568 - @Sumaya_875
🕊3
Showing the 12 most recent of 20 posts we hold for @MirrorYapp. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 825,180 of 1,189,255entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
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.
Mentions
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.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@MirrorYapp named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@orange4582 named in 1 post, 8 August 2026 – 8 August 2026
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 8 August 2026 — this
entry's latest reading, not the date you are reading this.
“Mirror-Y” (@MirrorYapp), 937 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/MirrorYapp.
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.