柠柠 | 23岁 | 162cm | 42kg | B 📍 成都 彭州市 💰 10P | 16PP 🎯 鸳鸯浴、舌吻、69、口爆 兼职转全职 电报:@Ethan_vvy 频道:https://t.me/+qYzGdwAAF2YxYTRl 藏楼同发:直达链接 报告频道: 报告频道 狼友交流群:@rongcheng_travel 更多验证,尽在 @cdverify 成都本地车友验证

Channel
成都车友验证频道
@cdverify
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
38,732subscribers
+26,992 since we began measuring on 11 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002417404083 |
|---|---|
| Type | Channel |
| Username | @cdverify |
| Description | 成都本地交流分享 用户修车真实反馈与体验老师记录 同城车友|夜生活|长期更新 |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 4 October 2026 |
| Measurements held | 31 |
| Confirmed unchanged | 1 time, most recently 4 October 2026 |
| On Telegram | t.me/cdverify |
Topic
Other / unclassifiable — 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 61% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 4 Oct 2026, 06:00 | 38,732 | +1,908 |
| 25 Sept 2026, 10:58 | 36,824 | +2,944 |
| 18 Sept 2026, 23:21 | 33,880 | +732 |
| 16 Sept 2026, 17:37 | 33,148 | -1,345 |
| 14 Sept 2026, 21:19 | 34,493 | +691 |
| 13 Sept 2026, 07:58 | 33,802 | -157 |
| 11 Sept 2026, 12:37 | 33,959 | +3,174 |
| 8 Sept 2026, 20:41 | 30,785 | +1,983 |
| 5 Sept 2026, 14:56 | 28,802 | +583 |
| 3 Sept 2026, 14:55 | 28,219 | +819 |
| 2 Sept 2026, 06:26 | 27,400 | +282 |
| 1 Sept 2026, 09:12 | 27,118 | +3,372 |
| 31 Aug 2026, 11:06 | 23,746 | +300 |
| 30 Aug 2026, 12:44 | 23,446 | +795 |
| 29 Aug 2026, 12:57 | 22,651 | +221 |
| 28 Aug 2026, 15:44 | 22,430 | +1,710 |
| 27 Aug 2026, 14:24 | 20,720 | +442 |
| 26 Aug 2026, 17:53 | 20,278 | +739 |
| 25 Aug 2026, 14:17 | 19,539 | +1,470 |
| 24 Aug 2026, 16:53 | 18,069 | first reading |
Engagement
109 posts held, back to 11 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 69 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.85%
- avg views ÷ 38,732 subscribers
- Avg views / post
- 1,100
- 30 posts measured
- Reaction rate
- 0.166%
- reactions ÷ views · ER floor
- Posts in window
- 30
- of 109 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 22 of 30 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 October 2026 |
|---|---|
| Posts held | 109 (11 August 2026 – 3 October 2026) |
| Views total | 33,099 |
| Reactions total | 41 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 4 Oct 2026, 07:36 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
- ≈1,800
- Videos
- ≈256
- Links
- ≈240
Lifetime counters from Telegram’s own channel header, read 4 October 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
- 8m 59s
- Average length
- 10s
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
531 reactions across 93 posts, in 7 distinct kinds. The most used accounts for 27.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 147 | 27.7% | |
| 🔥 | 111 | 20.9% | |
| ❤ | 98 | 18.5% | |
| 🎉 | 57 | 10.7% | |
| 🥰 | 54 | 10.2% | |
| 👏 | 45 | 8.47% | |
| 😁 | 19 | 3.58% |
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 93 of the 109 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 531 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 109 most recent posts we hold, published 11 August 2026 to 3 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
【花名】#露露 【地址】#天府二街 【标签】#高新区 #南门 #御姐 #颜值 #大胸 #巨乳 #大D胸 #大长腿 【服务】#水中萧 #无套口 #毒龙 #舌吻 #胸推 #陪洗 #乳交 #舔胸 #舔蛋 #深喉 #女上位 #服务控 #良家 #紧湿穴 #深情69 #投入 #情趣内衣 #制服 #丝袜 #高跟 #水多 #配合 【车牌】@Lulu5226 【课费】6P/10PP #6/10 【评价】朝鲜族颜值老师,人照相似度高,身材高挑,前凸后翘,大长腿。奶子D,无科技,手感柔软。御姐感强,很有韩国明星的气质,好看耐看。进门就是护士制服,白丝接待,让你血脉喷张。帮洗帮擦干都很体贴。AB面,舌漫,舔咪咪都有,毒龙顶的深,时间久,舔蛋深喉口技相当的强。支持舔逼,小穴蝴蝶浅褐色,易出水,保养好,蛮紧。AA主动女上,进入时能感觉较紧,很润。女上两个大白兔跳起来很是好看。体位配合,骚话也多,日出感觉了,一直喊姐夫,别有一番情趣。喜欢体验服务控,喜欢…
【花名】#喵喵 【地址】#天府二街 【标签】#高新区 #南门 #御姐 #娇小 #颜值 #气质 #大胸 #大C胸 #身材控 #感觉车 #态度车 #自聊 【服务】#陪洗 #深喉 #深情69 #三件套 #亲蛋蛋 #吹箫 #调情 #毒龙 #胸推 #紧湿穴 #水多 #敏感 #舔胸 #粉嫩 #配合 #主动 #女上 #骚浪 #黑丝 #丝袜 #制服 #情绪价值 #高跟 #包夜 #外出 #上门 【车牌】@aaamiao456 【课费】6P/9PP #6/9 【评价】颜值即正义,颜值御姐更是不可多得。老师来自弗兰,颜值高,人照一致,真人生活照片,让你看到就想日,身材匀称,162,88公斤,偏瘦,但是胸有C,无科技,手感圆润饱满。进门先是精致妆容迎接,主动热情,陪洗体贴入微,洗的差不多了就任凭狼友发挥,有的狼友从背后顶着老师的屁股,rua老师大咪咪,弄的老师遭不住。床上服务更是霸道,基础服务全都有,口的很专业,无齿感,有包裹感,不是简单的舔,而是吮…
👍2👏1🥰1
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【花名】#糯米 【地址】#红牌楼 【标签】#武侯区 #南门 #御姐 #娇小 #JK #大胸 #大C胸 #身材控 #感觉车 #态度车 【服务】#陪洗 #舌吻 #深喉 #深情69 #三件套 #亲蛋蛋 #吹箫 #调情 #紧湿穴 #水多 #敏感 #粉嫩 #配合 #主动 #女上 #骚浪 #丝袜 #制服 #情绪价值 【车牌】@nuomi907 【课费】5P/8PP #5/8 【评价】老师人照一致,年龄26左右,身高160左右,体重48公斤左右,胸C很软,乳头粉色,颜值较高的嫩妹,服务有陪洗、口,舌吻,69等等。姿势很配合,水多很热很润有点小紧,老师叫声很真实且大反馈感很强,自来熟会聊天,给情绪价值。大胸确实安逸没有风尘感。嫩妹控,胸控的可以打卡! 已验证: 报告链接1 报告链接2 报告频道: 报告频道 狼友交流群:@rongcheng_travel 更多验证,尽在 @cdverify 成都本地车友验证
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【花名】#晴天 【地址】#成华区 【标签】#理工大学 #东门 #御姐 #自聊 #颜值 #排骨精 #感觉控 #腿控 #高挑 #模特 #大长腿 #冷白皮 #身材控 #感觉车 #态度车 【服务】#陪洗 #亲蛋蛋 #口爆 #kb #吹箫 #深喉 #舔胸 #深情69 #口莎 #舔蛋 #挑逗 #舌漫 #调情 #紧湿穴 #水多 #敏感 #配合 #主动 #女上 #良家 #敏感 #制服 #丝袜 【车牌】 @jingjiaren 【课费】7P/13PP #7/13 【评价】 老师人照相基本无差,年龄25岁左右,超模身高差不多175,尽显高挑,腿又长又直,体重100左右,可以说是白骨精类别,全身无赘肉,皮肤整体冷白皮,胸部挺拔有B+,纯欲风,网红模特御姐的形象,十分耐看。老师性格好不冷场,会聊天,情绪价值高。风尘感低,女友感强,服务中眼神诱惑,特别是裸口,很有感觉,边口还边用眼神挑逗你,让你欲罢不能,下面户型为小蝴蝶B水较多,豆豆突出颜色偏粉,花生…
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【花名】#小瑞 【地址】#天府二街 【标签】#高新区 #南门 #御姐 #颜值 #气质 #大胸 #大C胸 #情绪价值 【服务】#陪洗 #浅吻 #女上位 #舔胸 #过水 #舔咪咪 #温柔 #吸皮 #舔蛋 #舔咪咪 #胸推 #深喉 #毒龙 #服务控 #蝴蝶穴 #水多 #按摩 #女友感 #制服 #丝袜 #紧湿穴 #十指柔情 #热情 #投入 #配合 #外出 #上门 #包夜 【车牌】@xiaorui333521 【课费】6P/10PP #6/10 【评价】老师因为不小心撞死四只鸡,逃来成都发展。难得的高颜值广西老师,和照片基本无差别。说话有趣自来熟,很有情绪价值。身材前凸后翘,气质满分,加上精致妆容,路上看到估计都要升国旗。进门先是一个大拥抱,熟络的聊天和诱导的骚话中就开始rua,洗澡体贴入微,洗的干净,让你感觉又调皮又贴心。上床后开始舌漫,胸部、乳头、肚子、大腿、蛋蛋、肉棒,一点也不放过。调情功夫了得,舔蛋蛋还戏称先吃点荔枝,再来吃肉棒…
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【花名】#绿萝 【地址】#市中心 【标签】#锦江区 #南门 #御姐 #大长腿 #颜值 #气质 #外围 #奶头粉 #兼职 #模特 【服务】#陪洗 #鸳鸯浴 #舌吻 #女上位 #三件套 #过水 #舔咪咪 #温柔 #深情69 #敏感 #胸推 #深喉 #态度控 #服务控 #蝴蝶穴 #水多 #按摩 #女友感 #制服 #丝袜 #紧湿穴 #良家 #投入 #配合 【车牌】@lvluo520 【课费】7P/11PP #7/11 【评价】高颜值、高挑、自聊御姐老师,身材高挑有172,真正的大长腿,屁股很翘,标准模特体型,无赘肉,皮肤白嫩,完美的衣架子。长相美丽且高级,报告里有的说像杨幂等明星,本地土著(正儿八经天府制造),加上是艺术类学科毕业,气质无法复制。照片随便一张都是女神海报级别,路上回头率刷刷的。胸B但是挺,未生育,奶头又小又粉。会找话题聊天消除陌生感,话题有趣,表现可爱,E人福音。服务过程温柔,感性,大蟒蛇管够,是那种女友要吃干你,有感…
❤1👍1🥰1
【花名】#幼辞 【地址】#驷马桥 【标签】#成华区 #驷马桥 #李家沱 #东门 #北门 #嫩妹 #巨乳 #大E胸 #大长腿 #颜值 #外围 #高挑 #兼职 【服务】#陪洗 #女上位 #全自动 #三件套 #过水 #温柔 #敏感 #胸推 #深情69 #浅吻 #深喉 #态度控 #服务控 #蝴蝶穴 #水多 #按摩 #女友感 #制服 #角色扮演 #紧湿穴 #良家 #投入 #配合 【车牌】@youci888 【课费】7P/11PP #7/11 写报告-1 【评价】弗兰辣妹子,高颜值(左下第一张疲倦的无美颜照片,敢给我这种照片也没谁了),高挑嫩妹,身材凹凸有致,真的是巨乳!大E胸,胸型挺拔,奈头小而粉嫩,手感软糯。高挑大长腿,细腰屁股有肉,皮肤光滑白嫩。会聊天,自然熟,说话声音很嗲,有情绪价值。服务细致,陪洗,口活细致温柔,舔🥚,深喉、锁喉熟练,另外还有角色扮演。支持女上位,上去后就化身电动小马达,分分钟让你缴械。逼紧水多且滚烫,非常会夹。…
❤1👍1
Showing the 12 most recent of 109 posts we hold for @cdverify. 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 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.
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 4 October 2026 — this entry's latest reading, not the date you are reading this.
“成都车友验证频道” (@cdverify), 38,732 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/cdverify.
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.