【成都海王修车】 花名: #于晚晚 车牌: @yuwanwan5201314520 地址: #市中心 价格: 800P/1300PP 优惠情况:暂无 ⭐️类型: #颜值车 #感觉车 #8P #自聊 #冷白皮 #毒龙 #深喉 #巨乳 锐评:年龄25左右,身高160 体重50kg左右,身材匀称。大胸G杯,不下垂,A4腰,完美s型身材。陪洗 胸推 按摩 毒龙 乳交 角色扮演等(无舌吻69)颜值御姐,极品身材,态度好 ,口技厉害,大G奶,手感好,乳交舒服,体验感强烈。服务多,玩法多样化 ,三点粉,胸大腰细,s型身材,胸控可以无脑冲。 https://t.me/chengduhaiwangxiuche

Channel
成都海王修车社区已验车库(备用)
@chengduhaiwangxiuchecheku
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Citations · Cite this entry
21,111subscribers
+23 since we began measuring on 9 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001550354152 |
|---|---|
| Type | Channel |
| Username | @chengduhaiwangxiuchecheku |
| Created | Between 1 August 2021 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 9 November 2026 |
| Measurements held | 60 |
| Confirmed unchanged | 1 time, most recently 9 November 2026 |
| On Telegram | t.me/chengduhaiwangxiuchecheku |
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 72% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 9 Nov 2026, 16:09 | 21,111 | -6 |
| 8 Nov 2026, 09:54 | 21,117 | -3 |
| 7 Nov 2026, 01:50 | 21,120 | +5 |
| 6 Nov 2026, 03:38 | 21,115 | -9 |
| 5 Nov 2026, 05:07 | 21,124 | -6 |
| 4 Nov 2026, 03:25 | 21,130 | +2 |
| 3 Nov 2026, 03:31 | 21,128 | -6 |
| 2 Nov 2026, 02:58 | 21,134 | -14 |
| 1 Nov 2026, 01:17 | 21,148 | -27 |
| 30 Oct 2026, 23:37 | 21,175 | +9 |
| 30 Oct 2026, 02:48 | 21,166 | -4 |
| 29 Oct 2026, 00:01 | 21,170 | -8 |
| 27 Oct 2026, 20:37 | 21,178 | -12 |
| 26 Oct 2026, 20:47 | 21,190 | -7 |
| 26 Oct 2026, 00:07 | 21,197 | -12 |
| 25 Oct 2026, 00:27 | 21,209 | +5 |
| 23 Oct 2026, 21:20 | 21,204 | +4 |
| 22 Oct 2026, 21:07 | 21,200 | -29 |
| 21 Oct 2026, 15:54 | 21,229 | -3 |
| 20 Oct 2026, 10:29 | 21,232 | first reading |
Engagement
69 posts held, back to 5 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 68 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.70%
- avg views ÷ 21,111 subscribers
- Avg views / post
- 358
- 18 posts measured
- Reaction rate
- 0.288%
- reactions ÷ views · ER floor
- Posts in window
- 18
- of 69 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 8 of 18 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 November 2026 |
|---|---|
| Posts held | 69 (5 August 2026 – 8 November 2026) |
| Views total | 6,444 |
| Reactions total | 9 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Nov 2026, 15:10 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
- Video runtime
- 1m 56s
- Average length
- 10s
Measured directly from 12 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
232 reactions across 44 posts, in 5 distinct kinds. The most used accounts for 65.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 153 | 65.9% | |
| 👍 | 69 | 29.7% | |
| 🔥 | 4 | 1.72% | |
| 🎉 | 3 | 1.29% | |
| 🥰 | 3 | 1.29% |
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 47 of the 69 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 232 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 69 most recent posts we hold, published 5 August 2026 to 8 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.
Telegram Stars
- Stars received
- 3
- across the posts below
- Posts paid on
- 3
- of 69 we hold a reading for · 4%
- Most on one post
- 1
- single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @chengduhaiwangxiuchecheku. 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 69 most recent posts we hold for this entry, published 5 August 2026 to 8 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 18 posts held from the last 30 days (0%) 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).
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_6356501220
【成都海王修车】 花名: 小艾 车牌: @xiaoaibby 地址: #驷马桥 价格: 600P/1100PP 硬件:身高172cm,体重55kg,皮肤正常黄,胸B+,属于大只马嫩妹,有舌钉。 优惠情况:暂无 ⭐️类型: #成华区 #嫩妹 #感觉车 #6P #代聊 #舌吻 #女友感 #大长腿 #身材车 锐评:妹子态度不错,微胖嫩妹梨型身材,服务不多好在听话,日感也好,喜欢微胖大只马嫩妹可以脑冲,身材属于炮架子。 https://t.me/chengduhaiwangxiuche
❤1
【成都海王修车】 花名: #徐冬冬 车牌: @yezi030305 车费: #600/P 1000/PP 位置: #衣冠庙 ⭐️类型: #成华区 #少妇车 #服务车 #态度车 #身材车 #自聊 硬件:年龄30+,身高155,体重100斤,正常黄皮,胸型D+大胸,软,奶头小,乳晕面积大,肉色偏粉,皮肤紧致没有纹身,下面小蝴蝶馒头B,毛量正常,内外水都多,有点小肚子。B紧,包裹感强,全身无纹身 锐评: 老师服务非常好,会所专业,特别是口技一流,毫无齿感,该有的服务例如DL,水中萧,推油,都是有的,吃服务和胸控的推荐,服务非常耐心。女上很卖力,主动制服丝袜,叫声骚气。 https://t.me/chengduhaiwangxiuche
🎉🎉🎉 开奖通知 🎉🎉🎉 🎰 你心中的皮皮纯来啦 ⚠️ 抽奖说明: 1.本次该奖品优惠券不可折现、不可转让、不可买卖;因炸号,退群,注销账号、恶意刷发言发送123字母、非正常聊天,找不到聊天记录等原因,超时未兑换等原的,不予兑奖! 2.本次活动优惠劵兑奖有效期为开奖后5天内,现金为开奖后2天内,逾期作废。 3·为避免小号、协议号、广告号,需有抽奖期间参与群对应任意车库中评论➕点赞,无评论不予兑奖 ⚠️ 如发现Ai机器人直接取消中奖资格不予兑奖,乱水群不兑奖。 🎅 联系领奖:@pipichun 🙋 参与人数:475 💫 鸿运加成:15票 💎x 1 中奖名单如下: 1. 李才醒(炸号版) 💫 x 1 奖品:单p半价劵 2. 今晚打老虎! 💫 x 1 奖品:pp200优惠劵 3. 忘忧草 忘忧草 💫 x 1 奖品:100元优惠劵 4. 海绵宝 奖品:100元优惠劵 5. Hi波肉 💫 x 1 奖品:58元口令红包 …
【成都海王修车】 花名:#suki 车牌: @suki0668 地址: #华宇广场 价格: 600P/1100PP 硬件:160左右,50kg,不胖不瘦,身材比较均匀,皮肤光滑白皙, 胸C。户型正常鲍鱼型,日感比较爽,水也多。 优惠情况:暂无 ⭐️类型: #锦江区 #少妇 #御姐 #感觉车 #6P #自聊 #舌吻 #女友感 #身材车 锐评:情商比较高的老师,身材有健身后的美感,日爽了反馈相当真实。配合度比较高,情绪价值也是阔以,性价比没得说 https://t.me/chengduhaiwangxiuche
【成都海王修车】 花名:#静怡 车牌: @JingYi798 地址: #交子大道 价格: 600P/1000PP 硬件:人照片差距小,基本就是本人,人不高,身高和那种萝莉一样不高1米五左右很瘦很瘦,皮肤小麦色,光滑细腻,胸c和身材比起来真的很显大,手感很舒服,奶头和石榴大小差不多,颜色褐色,捏起来有点硬,下面毛毛茂盛,外褐内粉,里面很滚烫,紧度适中,跨边上有点纹身。 优惠情况:暂无 ⭐️类型: #嫩妹 #颜值车 #态度车 #感觉车 #6P #代聊 #舌吻 #女友感 #身材车 锐评:老师颜值在线,本人也很乖,身材较好,前凸,胸大,服务较为丰富,在嫩妹里面真的数一数二有服务的了,口技娴熟,无齿感,下面滚烫,紧度适中,配合度高,也不催促,态度特别好,缺点真的是暂无。 总体来说小姐姐6p价位真的很值,颜值身材服务都有的嫩妹,性价比拉满了,推荐出击,早出击早享受。 https://t.me/chengduhaiwa…
❤1
【成都海王修车】 花名:#鹿米 车牌: @lumi778899 地址: #春熙路 价格: 700P/1200PP 硬件:人照8.5分,身高158cm,95斤左右,身材丰满型,胸大有C罩,皮肤光滑,淡黄色,无纹身无疤痕 优惠情况:暂无 ⭐️类型:#锦江区 #嫩妹 #萝莉车 #感觉车 #7P #代聊 #舌吻 #女友感 锐评: 优点:老师颜值还行,双马尾小萝莉,是身材丰满,皮肤顺滑的嫩妹,服务认真配合,女友感十足,水润紧致,日感不错 唯一缺点:民宿感觉隔音一般 https://t.me/chengduhaiwangxiuche
🎉🎉🎉 开奖通知 🎉🎉🎉 🎰 楚依依发红包了兄弟们 ⚠️ 抽奖说明: 1.本次该奖品优惠券不可折现、不可转让、不可买卖;因炸号,退群,注销账号、恶意刷发言发送123字母、非正常聊天,找不到聊天记录等原因,超时未兑换等原的,不予兑奖! 2.本次活动优惠劵兑奖有效期为开奖后5天内,现金为开奖后2天内,逾期作废。 3·为避免小号、协议号、广告号,需有抽奖期间参与群对应任意车库中评论➕点赞,无评论不予兑奖 ⚠️ 如发现Ai机器人直接取消中奖资格不予兑奖,乱水群不兑奖。 🎅 联系领奖:@CHyya8 🙋 参与人数:482 💫 鸿运加成:47票 💎x 8 中奖名单如下: 1. 怪盗 💫 x 2 奖品:现金红包88 2. 捉急得很 💫 x 1 奖品:现金红包58 3. chill 💫 x 1 奖品:现金红包28 4. yeban 💫 x 1 奖品:现金红包28 5. 奇葩 奖品:100元优惠卷 6. 李娅 一 💫 x 1 …
【成都海王修车】 花名:#琪琪 车牌: @CDqiqi4 地址:#金石路 价格: #600P /#1000PP 硬件:妹子人没有脸照不评价,真人看着乖,160cm,100斤,天然胸B,身上有点肉,白白嫩嫩的,无纹身,乳头小,户型紧凑,浅褐色,下面毛毛较少。昆感非常好,水多,正常紧度 优惠情况:暂无 ⭐️类型: #锦江区 #嫩妹 #颜值车 #身材车 #冷白皮 #感觉车 #态度车 锐评:妹子颜值不错,真人看着乖,比菜单稍微长胖了一点,身上白白嫩嫩的软软的抱着很舒服。态度很好,爱爱配合度也高,有舌吻,69,下面越做越湿,妹妹就是太害羞了,给人一种小鸟依人的感觉,妹妹还需要开发,会的比较少,才下水没多久. https://t.me/chengduhaiwangxiuche
【成都海王修车】 花名: #可乐 车牌: @kelemm520 车费: # 500/p 位置: #昭觉寺南路 ⭐️类型: #成华区 #少妇车 #服务车 #态度车 #5p #自聊 注: 老师人照8分,年龄30+,身高155,体重100斤,正常黄皮偏黄,胸型B,全身无纹身,蝴蝶B外褐内粉,毛量多不长,乳头花生米大小,乳晕正常不浮夸,服务内容陪洗,AB面,过水,DL,胸推,裸口,AA,B润,会夹,服务耐心不敷衍,基本就是管式全套服务,该有的都有,AA过程全程配合,姿势随便换,叫声真实骚气, https://t.me/chengduhaiwangxiuche
❤1
🎰 你心中的皮皮纯来啦 📮 参与条件: 🗺️ 区域限制:四川省;重庆市 🛡️ 必须设置用户名 🎫 加入-成都 皮皮纯🤪 🎫 加入-皮皮传送门. └💬 发言数大于 3 条 🎫 加入-成都海王修车社区已验车库 🎫 加入-成都海王修车社区 └💬 发言数大于 3 条 🎫 加入-成都大话修车已验证车库 🎫 加入-成都大话修车群 └💬 发言数大于 3 条 🎁 奖品内容: 💰️ 单p半价劵 x 1 💰️ pp200优惠劵 x 1 💰️ 100元优惠劵 x 2 💰️ 58元口令红包 x 1 💰️ 28口令红包 x 2 💫 鸿运加成:x 1 规则 ⚠️ 抽奖说明: 1.本次该奖品优惠券不可折现、不可转让、不可买卖;因炸号,退群,注销账号、恶意刷发言发送123字母、非正常聊天,找不到聊天记录等原因,超时未兑换等原的,不予兑奖! 2.本次活动优惠劵兑奖有效期为开奖后5天内,现金为开奖后2天内,逾期作废。 3·为避免小号、协议号…
Showing the 12 most recent of 69 posts we hold for @chengduhaiwangxiuchecheku. 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.
Posts edited after publishing
@chengduhaiwangxiuchecheku edited 2 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.
- First edit seen
- 1 September 2026
- Most recent edit
- 28 September 2026
Forward network
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 2 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.
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.
@chengduhaiwangxiuche · 24,66353 posts幸运抽奖导航
@LotteryNavChannel888 · 33,16516 posts成都大话修车群
@CDdahuaxiuche · 31,9896 posts成都大话修车已验证车库
@CDdhyzck1 · 77,2705 posts成都海王修车社区已验车库
@chengduhaiwangxiuchecheku1 · 14,8575 posts全国莞式全套会所
@The_Lure_of_Home01 · 7,7053 posts极搜🔍资源搜索@JISOU
@jisou2 · 2,551,9322 posts成都梦幻私影频道
@mhsy113 · 2712 posts成都修车•男团女团
@CDCnantuannvtuan · 40,4341 post皮皮传送门.
@PiPichun007 · 1,8591 post沈清梨的小圈圈😘
@qiruohan · 6,4221 post成都 皮皮纯🤪
@Temptation_to_Come_Home · 7,7001 post成都铜雀台mmk聊天群
@tongquetai444 · 7,4161 post成都铜雀台MMk选妃频道
@tongquetai888 · 16,2631 post成都铜雀台MMK反馈群
@tongquetai999 · 5,1341 post成都 楚依依 天府三街
@WHcuier · 6,0091 post武侯林若涵(自聊)
@WHlinqunian · 2,0621 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.
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 9 November 2026 — this entry's latest reading, not the date you are reading this.
“成都海王修车社区已验车库(备用)” (@chengduhaiwangxiuchecheku), 21,111 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/chengduhaiwangxiuchecheku.
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.