📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 花名:#兔兔 编号: 2458 车牌: @JJc887 课时费: #5/9 标签:#御姐车 #成华区 #代聊 #5P 地址:#昭觉寺 优惠:无 锐评:人照九分,年龄27,身高170,102斤,胸B+,有陪洗,大蟒蛇,69,口交技术很好,做爱有女友感,很放松,很投入,很骚。推荐喜欢女友感的兄弟们出击。 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤5
Signed 天涯海角

Channel
@CDnvtuancy
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Cite this entry
51,197subscribers
+1,328 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1002094530826 |
|---|---|
| Type | Channel |
| Username | @CDnvtuancy |
| Description | 本频道车牌均为已验证车牌,请广大狼友放心cj 。 希望你的每一次出击都是因为喜欢! 聊天群 : https://t.me/CDCnantuannvtuan |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 4 September 2026 |
| Measurements held | 27 |
| Confirmed unchanged | 1 time, most recently 4 September 2026 |
| On Telegram | t.me/CDnvtuancy |
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 21 August 2026 and assigned it the closest of 31 fixed categories, at 64% 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 |
|---|---|---|
| 4 Sept 2026, 06:01 | 51,197 | -33 |
| 2 Sept 2026, 17:45 | 51,230 | -125 |
| 1 Sept 2026, 17:52 | 51,355 | +25 |
| 31 Aug 2026, 19:25 | 51,330 | +46 |
| 29 Aug 2026, 22:02 | 51,284 | +42 |
| 28 Aug 2026, 22:33 | 51,242 | +93 |
| 28 Aug 2026, 00:04 | 51,149 | +62 |
| 27 Aug 2026, 03:27 | 51,087 | +55 |
| 26 Aug 2026, 03:34 | 51,032 | +117 |
| 25 Aug 2026, 06:23 | 50,915 | +71 |
| 24 Aug 2026, 03:44 | 50,844 | +149 |
| 22 Aug 2026, 13:43 | 50,695 | -38 |
| 21 Aug 2026, 02:16 | 50,733 | +76 |
| 20 Aug 2026, 02:48 | 50,657 | +60 |
| 18 Aug 2026, 23:15 | 50,597 | +130 |
| 17 Aug 2026, 19:35 | 50,467 | -33 |
| 16 Aug 2026, 19:07 | 50,500 | +58 |
| 15 Aug 2026, 10:19 | 50,442 | +126 |
| 14 Aug 2026, 03:05 | 50,316 | +113 |
| 12 Aug 2026, 23:14 | 50,203 | first reading |
128 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 63 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. It is computed over the 91 of 122 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 5 September 2026 |
|---|---|
| Posts held | 128 (5 August 2026 – 5 September 2026) |
| Views total | 97,991 |
| Reactions total | 431 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Sept 2026, 20:46 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 5 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 35 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.
454 reactions across 92 posts, in 7 distinct kinds. The most used accounts for 64.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 291 | 64.1% | |
| 👍 | 151 | 33.3% | |
| 🖕 | 5 | 1.10% | |
| 🌚 | 2 | 0.441% | |
| 🔥 | 2 | 0.441% | |
| 😁 | 2 | 0.441% | |
| 😱 | 1 | 0.22% |
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 96 of the 128 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 454 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 128 most recent posts we hold, published 5 August 2026 to 5 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.
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 花名:#兔兔 编号: 2458 车牌: @JJc887 课时费: #5/9 标签:#御姐车 #成华区 #代聊 #5P 地址:#昭觉寺 优惠:无 锐评:人照九分,年龄27,身高170,102斤,胸B+,有陪洗,大蟒蛇,69,口交技术很好,做爱有女友感,很放松,很投入,很骚。推荐喜欢女友感的兄弟们出击。 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤5
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#Cici 编号: 2457 车牌: @ci66880 课时费: #7/11 标签:#御姐车 #武侯区 #7P #代聊 #身材车 #大奶 地址:#省体育馆 优惠:无 锐评:人照8.8分,年龄23,身高165体重80,正常肤色手感光滑无纹身,胸C挺拔微科技,蝴蝶浅褐色水量适中较紧,服务不多但感觉不错 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤5
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名: #朵莉亚 编号:2456 车牌: @lili5364 课时费: #7/11 标签:#嫩妹车 #成华区 #7P #代聊 #身材车 #态度车 地址: #东郊记忆 优惠:无 锐评:人照8.8 身高162 体重 45 年龄 19 性格温柔 舌吻 陪洗 包子逼 陪洗 裸口 嫩妹 皮肤光滑 聊天交流 https://t.me/CDCnantuannvtuan
❤3
Signed 芹泽多么伟
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#叶汐 编号: 2364 车牌: @yexi188 课时费: #7/12 标签:#御姐车 #武侯区 #天府二街 #7P #自聊 #大长腿 #女友感 #态度车 地址:#天府二街 优惠:无 锐评:人照9分,人照基本一致。年龄22,165,95斤左右,皮肤滑嫩,🐻c手感很好,下面比较湿紧,口,蛇,颜值在线,身材绝佳,性格温柔,情绪价值足,态度很好,硬件软件各方面很不错 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤1
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#佑佑 编号: 2455 车牌: @yyouyouy6 课时费: #7/12 标签:#少妇车 #武侯区 #7p #代聊 #良家感 #服务车 地址:#武侯大道 优惠:无 锐评:人照差距稍大分本人瘦,年龄22身高165体重102,刚下水的良家少妇,身材一般,没有小肚子,胸a小穴水多紧,日感不错配合舒服 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤2
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#颜燕 编号:392 车牌: @yangyanmeme 课时费:5p 7pp #5/7 标签:#少妇车 #服务车 #5p #成华区 地址:#理工大学 锐评:人照相似度8,年龄29,态度好,服务好,身材匀称,颜值耐看,罩杯c,皮肤光滑,蝴蝶型 报告查看 https://t.me/kingword886 聊天交流 https://t.me/kingwordking
❤2
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#墨墨 编号: 2452 车牌: @momo580580 课时费: #7/12 标签:#御姐车 #态度车 #人工白虎 #武侯区 #7P #代聊 地址:#高升桥 优惠:无 锐评:人和照片8.8分,年龄24左右,颜值比照片更自然点,身高162左右,体重50kg左右,皮肤比较光滑,肤色偏白。态度还行,比较内向,奶子B,乳头正常,褐,手感不错。小穴白虎,毛剃过了,小穴紧度正常。无纹身,服务三件套,蛇漫正面,床上表现自然,爱爱很投入,高潮时候小穴很紧,水湿漉漉。喜欢的可以去打卡 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#Amy 编号: 2451 车牌: @Amy03999 课时费: #7/12原价 标签:#御姐车 #锦江区 #代聊 #7P 地址:#大观 优惠:无 锐评:人照九点五分,年龄23,身高165,90斤,胸C,有共浴舌吻,大蟒蛇,做爱有女友感 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤2
Signed 天涯海角
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% 花名:#冰冰 编号: 2450 车牌: @binbing16 课时费: #5/8 标签:御姐车 #锦江区 #5P #自聊 #bbw 地址:#三色路 优惠:无 锐评:人照8,年龄28,身高160体重113,黄皮光滑,天然熊e,户型一线天,水多紧,ab面服务,菜单有的都做,情绪价值可以,小骨架巨乳BBW 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
❤6
Signed 天涯海角
文东嫩妹御姐~工作室❗️❗️ 只做精品嫩妹御姐,专做回锅,各种服务车,嫩妹车,御姐车,SM,双飞,多P,外出,包夜……应有尽有日批找文东不走弯路 ❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️❗️ 约课联系:➡️ @Wendo02 选妃频道: https://t.me/nn3911 聊天双向群: https://t.me/nn93961
❤3
Signed 芹泽多么伟
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% 花名:#玲玲 编号: 2449 车牌: @xh123xha 课时费: #4/7 标签:#少妇车 #龙泉驿区 #4P #代聊 #良家感 #大蟒蛇 地址:#华大广场 优惠:无/报告减一 锐评:侧着那张人照8.5本人更自然,年龄28,身高165体重102,刚下水的良家少妇,热情健谈感觉很自然,身材皮肤都保养不错,匀称身材一点点小肚子,胸C手感柔软,小穴水多紧还会夹,日感好配合舒服 🦋萝卜青菜,各有所爱🦋 聊天交流 https://t.me/CDCnantuannvtuan
👍2🔥2
Signed 天涯海角
📊 2条车评 写报告 好评 100% 中评 0% 差评 0% 花名:#畅歌 编号: 2448 车牌: @azi333999 课时费: #5/8 标签: #御姐车 #态度车 #大蟒蛇 #感觉车 #服务车 #人工白虎 #武侯区 #5P 地址:#天府三街 优惠:无 锐评:老师27岁,服务很好,人照7.5,毒龙堪称一绝,无敌大毒龙,可🐍,身高162,体重60,老师舌头贼灵活,服务全,能夹会吸,服务态度也不错有耐心,身材一般有小肚子,胸有d,手感圆润,乳头偏大褐色,乳晕不大,整体身材属于微胖类型,有点肚子,下面为蝴蝶户型,颜色偏褐色,湿度一般,紧度为紧,周围毛量偏多,日感挺不错,包裹感好。服务有陪洗、水中萧、舌吻,胸推、AB面过水、服务相当不错,爱爱配合度高!该老师属于少妇服务车,皮肤正常肤色爱爱反馈真实,下面也比较水润和紧实;主打服务,毒龙很不错,开5的价格推荐服务控的狼友打卡! 🦋萝…
❤2
Signed 天涯海角
Showing the 12 most recent of 128 posts we hold for @CDnvtuancy. 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.
@CDnvtuancy edited 1 post 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.
@CDnvtuancy 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.
References a handle that is not a live channel — we have no record it ever was one.
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 4 September 2026 — this entry's latest reading, not the date you are reading this.
“成都女团已验证成员” (@CDnvtuancy), 51,197 subscribers as measured 4 September 2026. Telegram Register, tgregister.com/channel/CDnvtuancy.
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.