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Channel

🅥武汉老师车评🅥

@whlou4

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

42,965subscribers

+37,792 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1004303426158
TypeChannel
Username@whlou4
Description老师榜 @wuhanhua1 黄鹤楼 @wuhanlou 东湖群 @whlou 聊天技术 @whlou6 报告频道 @wuhanhua2 投诉 @millyne1 修车驾校 @carlugui 黑车曝光 @hijackcar
CreatedBetween 1 June 2026 and 7 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 November 2026
Measurements held58
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/whlou4

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 89% 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 the other topics.

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 in near-verbatim form on 2 other registered channels. This entry also sits inside a group of 6 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. 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)
Posted firstThenOverlapGap
@wuhanhua1/2073824 Aug 2026, 14:20 UTC@whlou4/5509 · this entry24 Aug 2026, 14:20 UTC1.00under a minute
@wuhanhua1/2079325 Aug 2026, 10:03 UTC@whlou4/5598 · this entry25 Aug 2026, 10:03 UTC1.00under a minute
@wuhanhua1/2094928 Aug 2026, 07:04 UTC@whlou4/5855 · this entry28 Aug 2026, 07:04 UTC1.00under a minute
@wuhanhua1/2095428 Aug 2026, 07:05 UTC@whlou4/5860 · this entry28 Aug 2026, 07:05 UTC1.00under a minute
@wuhanhua1/236513 Oct 2026, 14:19 UTC@whlou4/9704 · this entry3 Oct 2026, 14:19 UTC1.00under a minute
@wuhanhua1/238897 Oct 2026, 14:40 UTC@whlou4/10112 · this entry7 Oct 2026, 14:40 UTC1.00under a minute
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@wuhanhua1148 (8/8 hand-verifiable sample passed)1.00under a minute@wuhanhua1 (144–4)
@wuhanhua28 (8/8 hand-verifiable sample passed)1.003 minutesthis entry (6–2)

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. 133 of the 133 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 1,849 comparable posts for this entry, running 7 August 2026 to 12 November 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).

Of the group of 6 channels, the one whose matching posts we hold earliest is @wuhanhua2. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_copy · clone_mutual, last confirmed 13 November 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.

Channels linked by matching posts

This channel is in a group of 6 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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

5,17342,96524,0697 August 2026 — 5,173 subscribers8 August 2026 — 5,178 subscribers11 August 2026 — 5,285 subscribers14 August 2026 — 7,599 subscribers17 August 2026 — 10,394 subscribers18 August 2026 — 11,202 subscribers19 August 2026 — 12,312 subscribers20 August 2026 — 13,103 subscribers21 August 2026 — 13,861 subscribers22 August 2026 — 14,496 subscribers24 August 2026 — 15,543 subscribers25 August 2026 — 16,197 subscribers26 August 2026 — 17,004 subscribers27 August 2026 — 17,729 subscribers28 August 2026 — 18,474 subscribers29 August 2026 — 19,313 subscribers30 August 2026 — 20,267 subscribers1 September 2026 — 21,023 subscribers2 September 2026 — 21,555 subscribers3 September 2026 — 22,281 subscribers5 September 2026 — 23,547 subscribers8 September 2026 — 25,820 subscribers11 September 2026 — 27,780 subscribers13 September 2026 — 28,837 subscribers14 September 2026 — 29,755 subscribers16 September 2026 — 30,553 subscribers18 September 2026 — 31,016 subscribers25 September 2026 — 35,271 subscribers4 October 2026 — 37,071 subscribers8 October 2026 — 37,618 subscribers12 October 2026 — 38,397 subscribers14 October 2026 — 38,583 subscribers15 October 2026 — 39,009 subscribers16 October 2026 — 39,143 subscribers17 October 2026 — 39,259 subscribers18 October 2026 — 39,430 subscribers19 October 2026 — 39,499 subscribers20 October 2026 — 39,605 subscribers21 October 2026 — 39,641 subscribers22 October 2026 — 39,450 subscribers23 October 2026 — 39,424 subscribers24 October 2026 — 39,384 subscribers25 October 2026 — 39,362 subscribers26 October 2026 — 39,340 subscribers27 October 2026 — 39,553 subscribers28 October 2026 — 39,939 subscribers29 October 2026 — 40,015 subscribers30 October 2026 — 40,198 subscribers1 November 2026 — 40,107 subscribers2 November 2026 — 40,431 subscribers3 November 2026 — 40,690 subscribers4 November 2026 — 41,039 subscribers5 November 2026 — 41,442 subscribers6 November 2026 — 41,765 subscribers7 November 2026 — 42,528 subscribers8 November 2026 — 42,218 subscribers9 November 2026 — 42,086 subscribers11 November 2026 — 42,965 subscribers7 August 202611 November 2026
58 measurements spanning 96 days, net +37,792. 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”.
Measurement log — every subscribers count we have recorded, most recent 20 of 58
Measured (UTC)SubscribersChange
11 Nov 2026, 21:4742,965+879
9 Nov 2026, 21:1042,086-132
8 Nov 2026, 15:5142,218-310
7 Nov 2026, 06:0842,528+763
6 Nov 2026, 07:1041,765+323
5 Nov 2026, 07:1041,442+403
4 Nov 2026, 03:2141,039+349
3 Nov 2026, 03:5840,690+259
2 Nov 2026, 02:1140,431+324
1 Nov 2026, 00:1740,107-91
30 Oct 2026, 21:0640,198+183
29 Oct 2026, 19:5140,015+76
28 Oct 2026, 17:5939,939+386
27 Oct 2026, 18:1039,553+213
26 Oct 2026, 18:5839,340-22
25 Oct 2026, 20:3539,362-22
24 Oct 2026, 19:4739,384-40
23 Oct 2026, 21:0839,424-26
22 Oct 2026, 18:3839,450-191
21 Oct 2026, 11:1639,641first reading

Engagement

1,917 posts held, back to 7 August 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 149 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.207%
avg views ÷ 42,965 subscribers
Avg views / post
88.8
794 posts measured
Reaction rate
0.978%
reactions ÷ views · ER floor
Posts in window
794
of 1,917 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 152 of 794 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 13 November 2026
Posts held1,917 (7 August 2026 – 13 November 2026)
Views total70,528
Reactions total158
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Nov 2026, 16:48 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
≈6,760
Videos
≈976
Links
≈7,040

Lifetime counters from Telegram’s own channel header, read 13 November 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.

Video runtime
9m 26s
Average length
11s

Measured directly from 53 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

188 reactions across 173 posts, in 5 distinct kinds. The most used accounts for 53.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍10153.7%
❤8344.1%
👎21.06%
👏10.532%
🔥10.532%

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 183 of the 1,000 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 188 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 7 October 2026 to 13 November 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

Telegram’s own ‘edited’ marker: 6 of 794 posts held from the last 30 days (0.756%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

13 Nov 2026, 16:42 UTC9 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #7p #嫩妹 👤 老师:纯纯 (@wuchangchunbao) 🔗 主页: t.me/wuhanhua1/27117 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 昨天来了一次 今天来2刷了 第一次二刷同一个老师 纯纯老师 确实是我喜欢的妹妹风格 比较干净青春有活力 挺好看的 喜欢纯纯 下次还来 服务满意 给个9分吧 10分怕骄傲 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-11-13 23:38 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whlou7 车评报告 @whl…

13 Nov 2026, 16:12 UTC41 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #硚口 #大胸#服务 #包夜#舌吻#毒龙#98#御姐 👤 老师:白蝴蝶 (@dg1264) 🔗 主页: t.me/whlou1/825?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 白老师,从上楼就服务就开始了,上来先嘘寒问暖,亲口喂你吃水果,喜欢喝什么水,然后桌上摆的都是吃的,喝的诚意拉满。进入服务环节,全程帮你脱衣服,不用自己动手,帮你洗全身,然后跪式服务,日式凳浴,从手指放到脚趾头,全都给你洗的干干净净的。到床上就开始幻想体验,放上轻音乐,一边听着舒缓的音乐,放松全身,蒙上眼睛,戴上眼罩,然后白老师开始给你讲故事,在你身上做服务,冰火两重天,蜻蜓点水,水晶之恋,蜜蜂采蜜,360度无死角螺…

13 Nov 2026, 16:12 UTC35 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #大胸 #欢乐大道 #洪山 #御姐 #大凶 #毒龙 #5p #8pp 👤 老师:小鱼儿 (@zihan5201314) 🔗 主页: t.me/wuhanhua1/26703 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 下雨天终于约到小鱼儿姐姐,首先第一次被她吸引是她的声音,太有女人味啦,我特有姐姐控或者妈妈控,从小也希望有个姐姐,见到小鱼儿老师,心情很紧张,第一次约姐姐类型,哇靠,真的好欲好欲呀,大胸部,肥臀,加上有点肉的长腿,还穿上黑丝配高跟鞋,说给我优惠一张,4百而已,妈呀,这也太爽啦,拉到沙发,直接把我推倒,给我摸唧唧,我捏她的大奶奶,好有肉感,老师把我的头夹在她的两个小皮球中间,差点呼吸不过来,…

13 Nov 2026, 16:09 UTC28 viewsread 13 November 2026
Photo

🔥武汉95–98全裸毒龙五套口爆 单选公寓 不满意可换可走🔥 课费: 😕.口一次手一次70分钟5️⃣5️⃣0️⃣ 😢.做一次口一次70分钟1️⃣1️⃣0️⃣0️⃣ 服务流程:69舌,毒龙,共浴,阴推毛扫,与客人互动,情趣挑逗,果冻漫游,风游全身,吸皮刮痧,滚水漫游,泰式胸揉,激情臀推,冰火两重天 暴力撕袜 舌滑全身,玉女吞珠,龙入仙境, 应有尽有 安全稳定 营业位置:汉口 汉阳 武昌 洪山 南湖 光谷 徐东 还有更多位置请私聊 营业时间 13.00——2.00(全年无休 一直都在) 高端外围兼职学妹 每天更新 @tianzhilan88888 ✔️ ✔️ ✔️ 武汉三镇老师好评报告: t.me/+FR3To9hYc5c2Njg1 ✔️ 专业客服: @tianzhilan88888 ✔️ 双向联系人: t.me/Laizhilan_bot ✔️ 交流群: t.me/+FR3To9hYc5c2Njg1…

13 Nov 2026, 16:02 UTC37 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #汉街 #御姐 #5p 👤 老师:静怡 (@jinghiyi65) 🔗 主页: t.me/wuhanhua1/26812 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 静怡老师约了两次了,总体评价:骚,真骚,绝对值得冲!约好妹子后,按照妹子指引,直接进屋,妹子👠+性感丝袜+情趣内衣已经等着了,各种语言肢体挑逗,让人欲罢不能,然后冲澡,妹子给擦干后,在浴室门口的镜子面前就又开始挑逗了,然后吹,接着妹子拉着我的手,直奔卧室,又是吹,又是毒龙,服务到位,挑逗到位,戴套,开干,传教士,后入,前戏太足了,没几分钟就交代了,然后妹子回笼萧,又各种撩骚,洗澡,走人。值得再冲! ━━━━━━━━━━━━━━ 🙋 …

13 Nov 2026, 15:52 UTC40 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #洪山 #光谷 #御姐 #6p #兼职 #上门 👤 老师:小清儿 (@Xeeriu779) 🔗 主页: t.me/wuhanhua1/24161?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 御姐类型 身材很高挑。奶子白挺。 服务不错 👅的很舒服。提前开好空调。房间都有地毯 很贴心 还有事后萧。还给按摩了一下。真的很不错的一次出击 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-11-13 22:50 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whlou7 车评报告 @whl…

13 Nov 2026, 15:52 UTC34 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #6p #大胸 #御姐 #服务 👤 老师:紫烟 (@ziyanyan345) 🔗 主页: t.me/wuhanhua1/22439 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 今天下午就约了紫烟妹妹晚上的pp课,进门妹妹情趣内衣迎接,换鞋,缠绵,妹妹一直在我身上游走,差一点点没忍住就直接口爆了,脑子里过了一遍烦心事才忍住。接着戴套,妹妹上马,还是没坚持两分钟就交货了。接下来就是洗浴,妹妹在门口迎接,帮我擦干的同时口也没闲着,直接含进去了,爽得一匹😋😋。 接着就是上床,先按摩,胸推,接着就是毒龙了,我靠,爽的不要不要的。接着就是正面,先游走一遍,直接69,差一点点又没忍住,脑子里面又走马灯一遍。妹妹…

13 Nov 2026, 15:42 UTC44 views1 reactionsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #江汉 #御姐 #6p 👤 老师:米娜 (@minana369) 🔗 主页: t.me/wuhanhua1/26988 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 虽说今天下雨,还是约到老师了,看评价真不错,我也去探探怎么个事,见到老师,比照片好看,还年轻,也很热情,甜妹的笑容,脱下衣服,全身很白,下面毛少馒头穴,一线天,骚话连篇,口活一流,这价钱也值啦,希望老师一直对我优惠一张,真的心动啦! ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-11-13 22:40 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou …

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13 Nov 2026, 15:42 UTC40 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #硚口 #大胸#服务 #包夜#舌吻#毒龙#98#御姐 👤 老师:白蝴蝶 (@dg1264) 🔗 主页: t.me/whlou1/825?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 白老师,从上楼就服务就开始了,上来先嘘寒问暖,亲口喂你吃水果,喜欢喝什么水,然后桌上摆的都是吃的,喝的诚意拉满。进入服务环节,全程帮你脱衣服,不用自己动手,帮你洗全身,然后跪式服务,日式凳浴,从手指放到脚趾头,全都给你洗的干干净净的。到床上就开始幻想体验,放上轻音乐,一边听着舒缓的音乐,放松全身,蒙上眼睛,戴上眼罩,然后白老师开始给你讲故事,在你身上做服务,冰火两重天,蜻蜓点水,水晶之恋,蜜蜂采蜜,360度无死角螺…

13 Nov 2026, 15:12 UTC56 viewsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #硚口 #御姐 #4p #服务 👤 老师:贝贝 (@waq396) 🔗 主页: t.me/wuhanhua1/25544 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 妹子很热情,服务周到,环境也不错,洗完澡出来帮我拿浴巾,还是很有服务意识,服务杠杠的,要不是赶时间,怎么说也要来两次的。下次再约哦。感谢平台推荐👍👍 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-11-13 22:11 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whlou7 车评报告 @whlou4 查找老师

13 Nov 2026, 14:32 UTC76 views1 reactionsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #硚口 #7p #嫩妹 #汉口 👤 老师:小糖果 (@doszuh122) 🔗 主页: t.me/wuhanhua1/27111 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★☆ 4/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★☆ 4/5 └ 📷 人照:★★★★☆ 4/5 📝 评价内容: 老师很温柔,下面有沐浴露的香味,很细心。69的时候把老师舔高潮了,应该是真的,按都按不住,听起来非常爽,最后也是传统体位直接出水,都不想换姿势,攒了一周的全部释放,非常舒服 ━━━━━━━━━━━━━━ 🙋 评价人:ya lan 🕒 时间:2026-11-13 21:31 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whlou7 车评报…

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13 Nov 2026, 14:22 UTC117 views1 reactionsread 13 November 2026

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #洪山#蛇 #大胸 #口暴 #毒#御姐 👤 老师:薰衣草 (@xx55667789) 🔗 主页: t.me/whlou1/887 ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 下雨☔️闲来无聊看到老师,就发了消息,约好时间,准点到指挥上楼。进门看到老师的颜值身材就知道没来错,是我喜欢的类型御姐风。立马交了水费,直接进入流程,陪浴,全程基本不用自己动手,体验很好。薰衣草全程不敷衍。贴心服务很周到。 喜欢御姐骚妇的直接来就行 超级骚 会玩 水多 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-11-13 21:18 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 …

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Showing the 12 most recent of 1,917 posts we hold for @whlou4. 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.

Republished by 70 registered channels. The 48 listed are the ones that have forwarded the most posts; the rest are counted here but not each listed.

白蝴蝶快乐小屋
@dg12648 · 4,719
12 posts
九九 个人开课
@NN22886 · 1,303
8 posts
媛媛的后花园
@jshswjwjjsj · 291
7 posts
君君的小蜗居
@junjunde · 1,047
7 posts
小丸子在武汉
@xwzziliao666 · 1,263
7 posts
小葡萄🍇的闺房往事
@WXFC125 · 2,163
6 posts
露露后花园
@whlulum · 1,475
6 posts
小呢的卧室
@Kele898966 · 293
5 posts
黛玉的小窝
@daiyudexiaowo · 3,711
5 posts
全国莞式全套会所
@xhdbdbi · 1
5 posts
武汉 柔柔的小窝
@youyou12305 · 885
5 posts
小野猫的小窝
@zmmzaayyy · 437
5 posts
顺子的小屋🏠
@aabb117712 · 1,584
4 posts
百合瑜伽馆🏠
@baiheuu · 1,335
4 posts
果子🍋的私密空间
@ccguozi · 252
4 posts
娜塔莎kkz
@jdhhdhhdhbdb · 255
4 posts
💧木木湿哒哒的小花园🌸
@mumu040526 · 102
4 posts
宁宁的朋友圈
@shsijb · 1,124
4 posts
Lori
@xiaoxi184 · 1
4 posts
江城筱钰儿🌸
@xiaoyuer0404 · 647
4 posts
静静的小屋
@xjing123456 · 1,205
4 posts
猪儿虫的秘密花园
@zhuerchong33443 · 242
4 posts
武昌晓晓频道
@dssdfeggh63 · 363
3 posts
涂涂的后花园
@ttxbbo · 427
3 posts
兔女郎的后宫
@tutunld · 369
3 posts
🅥武汉老师报告🅥
@wuhanhua2 · 17,637
3 posts
小敬的小家
@xj2088 · 1,864
3 posts
妍妍的秘密花园
@Huangyanyan9 · 1,462
2 posts
报告专用频道
@Minabaogao · 34
2 posts
缘缘的频道-
@hssjnjhdhdjjd · 265
2 posts
九月朋友圈
@jius34v · 84
2 posts
极限反差😘😘财迷
@jxfc028899 · 732
2 posts
光谷兼职个人开课
@meimei2698 · 820
2 posts
萌宝的🏠
@mengbao_667 · 1,492
2 posts
念念的小窝
@niannian88856 · 1,919
2 posts
欣欣的后花园
@xiaoqi3258 · 428
2 posts
萌小萌🏠🏠🏠
@xmiuq · 81
2 posts
小鱼宝
@xyyy2007 · 1,356
2 posts
瑶瑶的频道
@yaoyao159951 · 441
2 posts
幼幼朋友圈🏠
@Dijkisi · 304
1 post
狸狸的朋友圈
@Liliqaq123 · 383
1 post
佳嘉的后宫(有课室)
@akkdk007 · 868
1 post
雅雅💗小窝
@dd125803 · 414
1 post
武汉江夏露露频道
@fhjbvdh · 26
1 post
D +个人:先付,纯中
@fuigduj57 · 328
1 post
小可的后花园
@hhggjibnj · 68
1 post
可可后花园
@kekewh0011 · 1,480
1 post
武昌晴晴频道
@khhsjkak · 299
1 post

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 89 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.

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.

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 11 November 2026 — this entry's latest reading, not the date you are reading this.

“🅥武汉老师车评🅥” (@whlou4), 42,965 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/whlou4.

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.