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Channel
魔都光明顶总舵入口
@shmdgmd
On this record: Topic · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
44,537subscribers
+8,029 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002292191236 |
|---|---|
| Type | Channel |
| Username | @shmdgmd |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 19 October 2026 |
| Measurements held | 43 |
| Confirmed unchanged | 1 time, most recently 19 October 2026 |
| On Telegram | t.me/shmdgmd |
Topic
Adult — 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 81% 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.
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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 19 Oct 2026, 18:48 | 44,537 | +308 |
| 18 Oct 2026, 21:54 | 44,229 | +124 |
| 17 Oct 2026, 20:27 | 44,105 | +70 |
| 16 Oct 2026, 20:25 | 44,035 | +97 |
| 15 Oct 2026, 18:19 | 43,938 | +38 |
| 14 Oct 2026, 15:05 | 43,900 | +102 |
| 13 Oct 2026, 05:50 | 43,798 | +211 |
| 8 Oct 2026, 23:58 | 43,587 | +706 |
| 4 Oct 2026, 16:57 | 42,881 | +1,016 |
| 26 Sept 2026, 19:58 | 41,865 | +409 |
| 19 Sept 2026, 17:38 | 41,456 | +429 |
| 17 Sept 2026, 09:21 | 41,027 | +332 |
| 15 Sept 2026, 11:57 | 40,695 | +507 |
| 13 Sept 2026, 18:57 | 40,188 | +114 |
| 12 Sept 2026, 02:01 | 40,074 | +161 |
| 9 Sept 2026, 15:17 | 39,913 | +459 |
| 6 Sept 2026, 05:18 | 39,454 | +305 |
| 4 Sept 2026, 02:00 | 39,149 | +153 |
| 2 Sept 2026, 13:02 | 38,996 | +76 |
| 1 Sept 2026, 10:57 | 38,920 | first reading |
Engagement
88 posts held, back to 19 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 147 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 5.24%
- avg views ÷ 44,537 subscribers
- Avg views / post
- 2,340
- 28 posts measured
- Reaction rate
- 0.132%
- reactions ÷ views · ER floor
- Posts in window
- 28
- of 88 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. It is computed over the 21 of 28 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 20 October 2026 |
|---|---|
| Posts held | 88 (19 July 2026 – 20 October 2026) |
| Views total | 65,398 |
| Reactions total | 68 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 20 Oct 2026, 18:14 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
- 166
- Videos
- 93
- Links
- 166
Lifetime counters from Telegram’s own channel header, read 20 October 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
- 4m 49s
- Average length
- 9s
Measured directly from 31 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
212 reactions across 67 posts, in 3 distinct kinds. The most used accounts for 97.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 207 | 97.6% | |
| 👍 | 4 | 1.89% | |
| 🥰 | 1 | 0.472% |
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 73 of the 88 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 212 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 88 most recent posts we hold, published 19 July 2026 to 20 October 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.
Recent posts
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 程一媱 老师电报号: @CYYshanghai 硬件: 颜值 3.75 (人照8.5分,参考验证视频。小御姐风,眼睛好看,真人眼睛比视频小点,04年天津妹子,自述播音专业女大,普通话标准) 妆品 3.88 (妆容精致不卡粉;妆造很用心,一整天后也能有较好的维持水准,效果不错) 皮肤 3.88 (白皮,手感嫩滑;无纹身。减肥导致皮肤松弛) 胸 3.75 (天然小b罩杯,胸型不错,手感软,乳头偏小,乳晕大小适中,颜色正常) 腰 3.38 (正面无小肚子;站姿平坦,坐姿整体状态松弛,手感一般,无锻炼痕迹) 臀 3.63 (屁股肉量一般,臀浪明显) 腿 4.13 (腿长适中,直,小腿细;身高不错,大腿围度适中,腿长比例适中) 足 4.00 (脚白,指甲修剪过,脚底状态不错,足底…
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 小茹 老师电报号:@xiaoru139 硬件: 颜值 4.08 (人照9分,颜值还不错,一眼能见的嫩,长相不算惊艳,但也耐看,配合妆后效果接近班花水准,白净,皮肤细腻,眼睛笑起来月牙,蛮好看的) 妆品 4.17 (整体妆品还是不错的,高光阴影细节处理的都不差,尾课略微有点卡粉;皮肤本身也比较好所以就打了个基础的底,我手抠了一下没很厚的粉) 皮肤 4.58 (暖白皮,正常黄皮偏白,整体细腻光滑,全身无纹身 ) 胸 4.67 (天然C+-D-左右,乳头乳晕小,色偏粉,手感非常好,白大软) 腰 3.92 (正常腰,腰身匀称,稍有一丢丢小肚子,基本看不见,无锻炼痕迹) 臀 4.17 (胯宽一般,但肉量还行,臀型整体比较翘,紧实不塌,屁股大,后入视觉很不错,宽度还行厚度不太够 ) 腿…
❤4
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 寒寒 老师电报号: @HanHan_0319 硬件: 颜值 4.21(真人比照片稍微瘦一点,眼睛卧蚕漂亮,鼻子挺,笑容自然;人照9分,03年重庆小美女,脸比较小,樱桃小嘴,耐看型,长的妩媚,越看越动人) 妆品 4.25(妆容非常完整精致,没有卡粉,睫毛自然;比较自然,不脱妆) 皮肤 4.08(黄白皮偏白,非常紧致,没有纹身有脐钉,毛孔较小,身上无疤痕,小腹有快速减肥导致的生长纹,背部偏滑,其余部位顶级光滑。) 胸 3.43(C,有科技,胸型较挺,大小匀称,乳头乳晕大小正常,颜色粉,形状很圆,手感比较结实,乳头小,乳晕稍大,揉搓反应很敏感,还可以乳交) 腰 4.46(腰身细,有健身马甲线痕迹,无赘肉;马甲线,小蛮腰,S曲线相当明显,腰臀比相当惊人;蜂腰马甲线) 臀 4.61(屁股又大又…
❤1
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 李慕婉 老师电报号: @LMW73 硬件: 颜值 4.47 (知性美女,头发扎起来的时候是略带端庄的美,长发披肩后更具诱惑感;最后一堂课了,让老师卸妆,清纯小嫩妹) 妆品 4.50 (妆品很好,尾课了效果也维持的很好,非常适合老师的脸型;眼睛和唇膏都很好看,妆品非常精致,让颜值再上升了一个档次) 皮肤 4.13 (皮肤很好,无瑕疵,肤色略黄,手感光滑细腻,全身无纹身) 胸 3.16 (天然A胸,乳头小,乳晕不大,颜色正常,手感柔软,从后面摸起来好玩) 腰 4.44 (小蛮腰,没有一点赘肉!) 臀 4.04 (小翘臀,骨盆正常宽度,手感柔软,肉虽然不多,后入也能看出臀浪) 腿 4.25 (腿得整体比例不错,长且直,肌肉紧实不松;运城的细长腿;光滑手感好,玩腿) 足 4.15…
❤4
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 多多 老师电报号: @SHduoduo 硬件: 颜值 4.08 (人照9分,参考验证视频。班花小美女,乖巧甜美,标准嫩甜妹;06年川妹子,声音温柔;真人脸略长,下巴稍微拉长了一点,鼻子没照片那么挺) 妆品 4.00 (约的头课,妆容精致不卡粉,符合甜美气质。妆化的也不错,虽然有点花了但是精致度还是有的) 皮肤 4.25 (白皙,手感滑。柔软。手腕上有个比指甲盖还小的纹身;皮肤非常白,手上有一个很小的字母纹身,问了妹子是纹了一点后悔就没纹了) 胸 4.08 (天然d罩杯,脂肪胸,胸大小不错,乳头乳晕偏大,颜色正常;就是是吊钟奶有点垂;手感软,rua起来感觉不错) 腰 4.08 (腰在整个人身体比较丰满的情况下还是不错的;腰部有点小肉肉,没有褶子,妹子本来有些微胖,但是腰的比列刚…
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 老师名字:小水 老师电报号:@xiaoxinren1314 硬件: 颜值 4.28(人照 8 分,高级网红脸。小尖脸,脸部曲线柔和,有魅惑感。鼻梁处露出一点点小雀斑痕迹,使得脸部整体很有高级感,同时脸上皮肤无比光滑细腻。鼻子、下巴、额头做过,但比较自然。) 妆品 4.28(夜店风格烟熏妆,黑色眼影,鼻子做高光修容,底妆白皙。本身良好的脸部皮肤状态导致妆感呈现效果非常好。) 皮肤 4.50(冷白皮,整体滑嫩,皮肤滑嫩紧致。无纹身,右胸下面 5cm 处一个肋鼻疤,不影响观感。) 胸 4.31(C胸,手感极好,软中带弹。乳头,乳晕适中,偏粉。胸型好看,挺拔轻微外扩,左右乳略微不对称。) 腰 4.06(无赘肉,腰线清晰,腹部平坦,有细微马甲线。扶腰,搂腰感极强。) 臀 4.31(胯宽中等,臀型圆润挺翘。抓捏手感软糯,拍之如云朵般…
❤1
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 诗诗 老师电报号: @shi112233abc 硬件: 颜值 4.5 (人照 8 分,与视频基本一致,耐看小圆脸,柔弱可人风,超可爱,感觉像漫画里走出来的美少女,青春气息满满;人照高颜小美女,巴掌脸,颜值很不错,眼睛大,五官精致) 妆品 4.50 (妆容精致服帖,与肤色无色差,近看有点卡粉,远看整体较好粉底贴合,尾课保持的仍然不错,脸上皮肤状态也很好) 皮肤 4.38 (黄皮偏白,手感细腻滑嫩,无明显皮肤问题,无纹身) 胸 4.38 (纯天然C杯,胸型略微外扩八字水滴脂肪奶,自然挺立,手感软弹,乳晕稍大,乳头正常,浅褐色较粉嫩) 腰 4.00 (细腰曲线明显,坐姿有小肚腩赘肉,站立平躺时基本看不见,微肉的恰到好处,后面曲线不错) 臀 4.63 (天赋蜜桃臀,翘,胯宽,肉感也…
❤8
抽奖黄浦 兔子牙 抽奖活动(编号L1791374397800F7A4F80F)已成功开奖: 创建人:柏林[7198140553] 已参与人数:372 中奖名单如下: 歆樱(@yxiang070707)[2089123976](奖品:单p半价)
"米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级)" 老师名字: 蕊蕊 老师电报号: @ruirui8686 硬件: 颜值 4.00(年轻,脸很小很嫩,人照九分,青春感,笑起来可爱良家;清新少女甜美型;清纯妹子,天然无风尘感,脸很小;嫩妹脸一个,五官不错) 妆品 4.14(妆造加分,服帖无卡粉,使得颜值进一步提升,脸蛋皮肤很滑;清新的淡妆,淡淡的粉没有色差,假睫毛也不长,整体素雅符合气质;妆品较素,较淡,粉底不多,无卡粉,妆品不错) 皮肤 4.46(白皮可见青筋,手感光滑细腻,全身无疤痕无纹身,白皙的黄白皮,手感细腻,后背略有些体毛;皮肤很白,且细腻) 胸 3.89(天然B+,乳头颜色粉嫩,乳晕小,整体手感Q弹软糯,乳头、乳晕不大,色粉) 腰 4.29(纤细腰肢,无明显赘肉,年轻肉体手感滑嫩、女上可见腹肌;腰细没有什么明显赘肉,腰线明显有腰窝,无…
❤3
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字: 汐汐 老师电报号: @ReneHart2012 硬件: 颜值 4.15(人照9分,脸小,没有整容痕迹,充满了青春荷尔蒙,五官都很小巧,嘟嘟小嘴。07年川妹子,婴儿肥,妈生脸,好看的甜妹,笑起来有酒窝;很嫩!不过眼睛没有视频这么大,五官属于比较柔和型,稍稍还没长开;违反常态的娃娃脸、幼嫩脸蛋犹如“人间 AI“, 幼嫩体的略椭圆小脸粉嫩、粉嫩伴随灵动大眼就像精灵一般,脸部皮肤状态不错) 妆品 4.25(青春淡妆;妆容精致不卡粉,脸上很光洁;嫩妹妆,卧蚕画的不错,很符合自己气质;淡妆面部显白皙,粉底适中较素,不需要过多的修饰尽显本嫩) 皮肤 4.25(正常黄皮微白一个色号,左手小手腕纹身,右大腿有纹身包腿,不low,皮肤细腻爽滑,标准嫩妹嫩度,肌肤软嫩滑,无明显疤痕) 胸 4.05(b+天然…
❤9
米其林2.0,硬件权重60%,软件权重40%,按照加权平均分予以评级,只针对妹子素质客观评价 (课室分仅供参考不计入个总分评级) 老师名字:蒂娜 老师电报号:@yajiexiao 硬件: 颜值 4.31(大御姐、风情万种,颜值还不错;人照9分,参考红衣视频。01年江苏人,短发御姐,大蜜风格,肋骨鼻,嘴唇厚实,大圈水准,卡姿兰大眼睛,卧蚕漂亮;脸型流畅,高鼻梁和饱满唇形极为抓人;水汪汪的大眼睛辨识度极高) 妆品 4.31(妆容精致,烈焰红唇,眼妆漂亮,艳丽适中;妆造与颜值匹配,底妆干净通透,眉形利落,眼妆通过卷翘睫毛和卧蚕放大双眼,唇色与整体冷艳风格协调;妆品拉高颜值,睫毛修长浓厚,卧蝉飞霞闪亮,面若白皙,粉底不薄,无明显卡粉) 皮肤 4.44(皮肤不错,正常黄皮偏白皙,肋骨鼻小疤。肤色均匀,手感滑嫩;整体光滑,无纹身,无明显疤痕;肌肤软嫩顺滑) 胸 4.63(大 D 小 E 天然大熊,挺拔柔软脂肪胸,乳头乳晕大小适中,颜色正…
❤4
Showing the 12 most recent of 88 posts we hold for @shmdgmd. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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 40 registered channels — 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
Named by
Channels on the register whose posts name this channel's handle.
@moduguangmingding2 · 57,433325 posts魔都光明顶教学课程展览室1
@moduguangmingding1 · 38,609126 posts魔都光明顶教学课程展览室
@moduguangmingdin · 29,655115 posts江浙沪集美榜单
@moduwaiwei · 7,86815 posts特工验证榜
@godagent007 · 20,8035 posts冰哥的米其林厨房
@icebteakitchen · 4,9894 posts魔都光明顶福利频道
@moduhuangmingdingfuli · 9,5553 posts魔都狼友作品鉴赏5
@modupiczuoping · 5,3433 postsTom猫的笔记
@Tomcatnotes · 2,3543 posts金桥越南人妻的小窝
@guai111555 · 2842 posts小王的Nature
@wangxiaochi99 · 7232 posts小倩同学💕
@xiaoqian0822 · 5692 posts💞 熙桐 甜妹纯欲 自聊
@ahz6898 · 5981 post沪杭精选入口频道
@hhjxchannel · 1,2321 post款款的联络站
@kjjnzdqwsjs · 21 post辣可可🌶️@小窝
@lemi66601 · 1,7921 post小龙女姑姑
@longnvgg6 · 7,7141 post瑞瑞三年级二班
@lx295352181 · 2,4171 post呆呆宝的🏠
@OoO147369 · 5241 post小茹的日常
@xiaoruder · 2831 post风陵渡口初相遇
@yangdaguo123 · 3571 post上海一站式贷款服务中心
@yizhanshidaikuan888 · 391 post🌙月光宝典3.0🌙
@yueguangbaodian4 · 3,2551 post知知的课表
@zhizhikb · 2,1791 post
Names
Channels on the register whose handles appear in this channel's posts.
@moduguangmingding2 · 57,43369 posts魔都光明顶中圈资源
@mdgmdzq · 6,9506 posts京沪同城❤️🔥高端甄选驿站
@cjfk888 · 1,1755 posts特工验证榜
@godagent007 · 20,8034 posts馨馨🦋【精品阁】旗舰店
@httxyj9998888 · 3,6584 postsMK体育
@MK888bot · 12,6884 postsMK体育—飞投版: MK.BET
@MKFT777 · 2,5104 posts东南亚资讯|聚焦
@rdsjo · 15,7454 posts魔都光明顶福利频道
@moduhuangmingdingfuli · 9,5553 posts🍵伯昌君的休假记录
@bochangjun · 10,1722 posts魔都狼友作品鉴赏5
@modupiczuoping · 5,3432 posts洋洋很开心
@aa85849188 · 2931 post上海4T怡红院 【探店】
@AAAAA999999999999998 · 3,3211 post魔都光明顶备用中圈频道
@gmddq2 · 1,5731 post全国包养萝莉/处女/学妹(广告频道)
@hushangsaoyawawa · 21 post军师甄选❤️🔥新手指南
@jinsheng5188 · 3751 post魔都光明顶教学课程展览室1
@moduguangmingding1 · 38,6091 post全国包养萝莉/处女/学妹(广告频道)
@westbooks0 · 11 post【极致欢愉】纯享射出spa
@xnlspahhh · 7,6061 post大头鸭 每日更新
@zzzz18580 · 4,4741 post
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
- 2
- 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
- 2
- vacant every time we have ever looked
@shmdgmd named 2 handles 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.
named in 9 posts, 8 August 2026 – 28 September 2026
named in 2 posts, 14 September 2026 – 15 September 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 19 October 2026 — this entry's latest reading, not the date you are reading this.
“魔都光明顶总舵入口” (@shmdgmd), 44,537 subscribers as measured 19 October 2026. Telegram Register, tgregister.com/channel/shmdgmd.
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.