📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #棠棠 🔗 车牌: @tang697 💰 价格: #8/14 📍 地址: #石羊场 🏷️ 标签: #武侯区 #石羊场 #颜值车 #御姐车 #大奶车 #态度车 #感觉车 #兼职 #自聊 #8P 🧾工兵锐评:年龄24左右,166-100左右,无露脸照片,不做相似度评价。真人颜值很高,很好的颜值车。奶子C+到D,很挺,一只手抓不住,手感很好,乳头小褐色。皮肤很光滑,紧致。有纹身。态度很好,健谈,有气质,御姐风。小穴内粉,毛量正常,很紧,日感很好,妹妹爱爱主动,能gc,反馈很棒,兼职,服务三件套,大蟒蛇,胸推,丝袜,69,调情。是个极品御姐车。适合喜欢高颜值御姐大奶车 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu

Channel
༺ཌༀ成都修车俱乐部•车库ༀད༻
@CD_julebu1
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
36,403subscribers
+3,395 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 | -1001951353503 |
|---|---|
| Type | Channel |
| Username | @CD_julebu1 |
| Description | ༺ཌༀ修车俱乐部ༀད༻ @CD_julebu ༺ཌༀ报告频道ༀད༻ t.me/Jlbbg |
| Created | Between 1 April 2023 and 31 October 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 9 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/CD_julebu1 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 15:36 | 36,403 | +456 |
| 12 Aug 2026, 18:33 | 35,947 | +405 |
| 11 Aug 2026, 16:55 | 35,542 | +417 |
| 10 Aug 2026, 19:32 | 35,125 | +442 |
| 9 Aug 2026, 19:41 | 34,683 | +597 |
| 8 Aug 2026, 19:56 | 34,086 | +448 |
| 7 Aug 2026, 18:53 | 33,638 | +630 |
| 6 Aug 2026, 20:11 | 33,008 | no change |
| 6 Aug 2026, 20:04 | 33,008 | first reading |
Engagement
43 posts held, back to 6 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 20 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.64%
- avg views ÷ 36,403 subscribers
- Avg views / post
- 598
- 43 posts measured
- Reaction rate
- 0%
- reactions ÷ views · ER floor
- Posts in window
- 43
- of 43 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 1 of 43 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 14 August 2026 |
|---|---|
| Posts held | 43 (6 August 2026 – 14 August 2026) |
| Views total | 25,704 |
| Reactions total | 0 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Aug 2026, 13:20 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
- ≈3,740
- Videos
- ≈300
- Links
- ≈813
Lifetime counters from Telegram’s own channel header, read 14 August 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
- 2m 01s
- Average length
- 11s
Measured directly from 11 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.
Recent posts
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #纯纯 🔗 车牌:@pipichun 💰 价格: #7/12 📍 地址:#省体育馆 🏷️ 标签:#武侯区 #省体育馆 #御姐车 #代聊 #7P 🧾工兵锐评:不错的御姐,比较主动有点S 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
📊 0条车评 写报告 好评 0% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #叶汐 🔗 车牌:@yexi188 💰 价格: #7/12 📍 地址:#天府二街 🏷️ 标签:#武侯区 #天府二街 #御姐车 #自聊 #7P #大长腿 #女友感 🧾工兵锐评:人照9分基本一致。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 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #棉棉 🔗 车牌:@MMya7810 💰 价格: #6/10 📍 地址:#天府二街 🏷️ 标签:#武侯区 #天府二街 #嫩妹车 #代聊 #6P #巨乳 #头部按摩 🧾工兵锐评:人照相似度9,年龄24,态度很好是那慢热型,服务水中大奶按摩,口,舔咪咪还会咬你的乳头,而且还有头部按摩很舒服,身材大奶子腰细,颜值9基本上和照片差不多少见的和照片差不多的老师,罩杯大大大E很不错的奶子软的很,皮肤比较白而且很丝滑,户型是馒头逼而且很润批比较浅不深但是日起来特别爽,而且老师叫声无比销魂,真的是厉害。 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #CC 🔗 车牌:@CC52010 💰 价格: #6/9 📍 地址:#天府一街 🏷️ 标签:#武侯区 #天府一街 #御姐车 #6P #代聊 #态度车 #舌吻 #大蟒蛇 🧾工兵锐评:23岁,人照9分,身高160,体重46kg,身材很棒,肤色较暗,皮肤手感光滑,罩杯b,奶头嫩,下面外褐里粉,水润湿滑,服务态度很好,舌吻调情主动配合,爱爱过程热情奔放,反馈足叫床声有诱惑力,日起来很带劲,值得推荐。 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #阿娇 🔗 车牌:@Nxa520 💰 价格: #7/11 📍 地址:#峰度天下 🏷️ 标签:#武侯区 #峰度天下 #御姐车 #感觉车 #大胸控 #自聊 #高新区 #丝袜 #情趣 #7P 🧾工兵锐评:人照相似度8分,年龄26左右,态度还不错,会聊天,服务比较主动,服务简单但是温柔仔细,主要是指划调情,舌头漫游,舔蛋口,爱爱,舌吻等。 身材娇小胸大屁股大,颜值耐看型御姐,罩杯c胸白乳头粉嫩,可惜科技胸,皮肤白皙丝滑,户型馒头批,毛量少,外褐内粉,水量充足又湿又热昆感还不错。 爱爱主动,聊天自然,配合度还可以,叫声性感就是略微有点痛苦面具,大蟒蛇敏感骚骚的,其他都没啥问题,不介意有点科技脸科技胸还是可以出击。 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_jule
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #云舒 🔗 车牌:@Yunshu263y 💰 价格: #5/8 📍 地址:#驷马桥 🏷️ 标签:#成华区 #驷马桥 #少妇车 #代聊 #5P #服务车 #车震 #颜射 #3t #口爆 #拍视频 #上门 #包夜 🧾工兵锐评:人照9分相似度,年龄32,态度很好,老师刚下海,服务还行,但是态度很好,身材不胖不瘦,B罩杯,皮肤还行,后入视觉良好,推荐兄弟们可以一试 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
🎰 俱乐部 & 美美一起启航🤘 📮 参与条件: 🌏️ 归属地 四川 🪪 必须设置用户名 🎫 加入-美美的朋友圈 🎫 加入-神秘的出击流水账纪实 🎫 加入-小天涯·日记 🎫 加入-༺ཌༀ成都修车俱乐部ༀད༻ └ 🔑 发送口令﹝万般美好,皆是美美﹞ ❗ 口令提示: 请先参与抽奖,再发送口令激活 🎁 奖品内容: 💰️ 100优惠券 × 3 💰️ 1500特价夜 × 1 💰️ 50口令红包 × 3 💰️ 俱乐部积分 666 × 3 💰️ 单P半价优惠券 × 1 ⚠️ 抽奖说明: 1.本次优惠券不可折现,优惠券兑奖有效期为开奖后3天内,逾期作废! 2.因炸号,退群,注销账号等原因,超时未兑换等原因的,不予兑奖! 3.中途退群退频道,乱水群都会取消中奖资格! 4.口令以及优惠券找美美宝宝 @APA68888 ,积分找 @xtya6 🔋 人品加成:⚡️× 9 规则 📅 开奖日期:(北京时间) 2026年08月15日 18
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #兜兜 🔗 车牌:@doudou1680 💰 价格: #7/12 📍 地址:#武侯区 #高升桥 🏷️ 标签:#嫩妹车 #代聊 #7P #大奶 🧾工兵锐评:人照相似度9分,年龄19,颜值还可以的嫩妹,态度不错能聊天,身材丰满不胖一点小肚子,正常肤色手感光滑胸口小纹身,天然大C手感柔软,乳头乳晕正常大小粉褐色,馒头粉褐色毛量正常,水量适中较紧爱爱敏感 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #茉莉 🔗 车牌:@moolillll 💰 价格: #7/12 📍 地址:#东郊记忆 🏷️ 标签:#成华区 #东郊记忆 #嫩妹车 #代聊 #7P #颜值车 #态度车 #三件套 🧾工兵锐评:去掉瘦脸人照一致。168/100,皮肤白净光滑无纹身。胸B柔软挺拔。蝴蝶逼逼又紧又湿。呻吟好听,主动又配合。值得一冲 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
📊 1条车评 写报告 好评 100% 中评 0% 差评 0% ༺ཌༀ成都俱乐部•认证老师ༀད༻ 🙋🏻♀️ 老师: #玲玲 🔗 车牌: @xh123xha 💰 价格: #4/7 📍 地址: #龙泉华大 🏷️ 标签:#龙泉区 #龙泉华大 #少妇车 #态度车 #感觉车 #兼职 #自聊 #4P 🧾工兵锐评:年龄28左右,165-110左右,颜值和侧卧着的照片9分像,颜值正常。奶子C,乳头褐色,而且小。皮肤很光滑,态度很好,健谈。小穴,毛少,很紧,很会夹,主动,兼职,会的服务不多,三件套,蛇纹。适合喜欢少妇感觉车的兄弟打卡 💃🏻如有补充或更正,欢迎大家留言指正 聊天大群 @CD_julebu
全城会所95 98🥰 单选 海选🥰 无套路 无定金 🥰不办卡 不充值 不强制消费🥰 现场选人 不满意可以换 营业时间:下午13:00至凌晨4:00 客服老派📢: @Caihua8880000 双向机器人📢: @Caihua111_bot 频道📢:https://t.me/Caihua888000 聊天群📢: https://t.me/CDDBQ_028
Showing the 12 most recent of 43 posts we hold for @CD_julebu1. 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.
Citation-graph rank
Citation-graph rank — 282,776 of 1,336,469entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 4 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.
@CD_julebu · 54,46532 posts保安
@abaoan_bot · 81,07230 postsLotteryBest抽奖导航
@lotterynav · 161,2573 posts小天涯·日记
@xtyrj · 3,4623 posts美美的朋友圈
@APA688888 · 812 posts成都柒月女女女女仆mmk私影体验馆
@cdnnnnpmmk · 1,4882 posts神秘的出击流水账纪实
@ClubCarousel · 1,1582 posts极搜🔍资源搜索@JISOU
@jisou2 · 1,398,8852 posts成都外围精选 阿米在线
@cdmigeww · 12,0241 post成都商K 真空游戏 换装场
@CDYL008 · 1001 post=͟͟͞♡成都修车会所[海选☻半套全套]
@GS_SJK · 32,7661 post蓝思的英雄团
@lansi5200 · 1,8391 post成都茉莉抓龙筋
@mlzlj3344 · 3,1431 post🔥小曲奇|成都MMK私影助教相册
@xiaoquqisiying · 1821 post全国包养萝莉/处女/学妹(广告频道)
@xiaotianya66666 · 91 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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“༺ཌༀ成都修车俱乐部•车库ༀད༻” (@CD_julebu1), 36,403 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/CD_julebu1.
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.