Channel
@cdrblck
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
6,913subscribers
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1003951477657 |
|---|---|
| Type | Channel |
| Username | @cdrblck |
| Description | 本群唯一客服 @lfgcgn1_bot 成都日不落：https://t.me/chendurbl 成都楼凤群 https://t.me/cdlfls 楼凤阁频道 https://t.me/cdrbl 日不落频道 https://t.me/cdrblck |
| Created | Between 1 April 2026 and 12 April 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 14 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 1 |
| On Telegram | t.me/cdrblck |
Growth history is still building. We hold one measurement for this entry. A trend needs at least two, taken days apart — so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Aug 2026, 19:03 | 6,913 | first reading |
4 posts held, back to 12 April 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 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 4 posts for this entry, the most recent from 11 July 2026. An engagement rate over an empty window would be a number about nothing.
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. Below Telegram’s rounding threshold, so these counts are exact.
Measured directly from 1 video 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.
5 reactions across 4 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 5 | 100.0% |
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 4 of the 4 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 5reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 4 most recent posts we hold, published 12 April 2026 to 11 July 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.
#小芳 #成华区 #御姐 #半套 #双飞 ✨005 车牌: @linzhij 👑课时费:6p(50min)10pp(90min)👑 👑#御姐车 #服务车 👑年龄:27身高：163体重：45kg🐻B👑 👑特色: 双飞 半套👑 👑服务: 鸳鸯浴 69 胸推 臀推 阴推 舔蛋 丝袜高跟 毒龙 情趣 👑 👑点评：皮肤细腻，身材匀称，个子虽然不算太高，胸天然b，形状好看。少数人比照片好看的老师，洞口小，缺点是英年早婚，腹部有伤疤，开五的话女菩萨，开六中等，实名推荐！
❤1
#小宝 #成华区 #御姐 ✨004 车牌: @eggdc15 👑课时费:6p(60min)10pp(90min)👑 👑#御姐车 👑#人工白虎 👑年龄:24身高：162体重：48kg🐻C👑 👑特色:腿长，乳交👑 👑服务:嫩妹三件套 乳交 👑 👑点评：长相有点异域风情，跟照片有个八分相似，说话声音有点夹夹，性子慢半拍，脾气良好，没有什么服务，有很多的纹身，有明显的小肚子，但身材丰臀肥乳，做爱动情，情绪价值给的很足，整体来说还是值得推荐的！ https://t.me/cdlfls
❤1
#轩儿 #成华区 #少妇 ✨003 车牌: @xuaner7118 👑课时费:5p(50min)8pp(90min)👑 👑#少妇车 👑年龄:27身高：160体重：50kg🐻d👑 👑特色:服务好，细枝硕果👑 👑服务:蛇吻，胸推，水中萧，毒龙👑 👑点评：标准服务车，态度好，胸大光滑，真胸手感好，细枝硕果，适合喜欢服务少妇的狼友，无明显缺点，实名推荐！ https://t.me/cdlfls
❤2
#辛怡 #高新区 #御姐 ✨002 车牌: @xinyixinyixin 👑课时费:5p(50min)8pp(90min)👑 👑#御姐车 👑#颜值车 👑年龄:28身高：162体重：50kg🐻d👑 👑特色:丰臀肥乳 颜值高👑 👑服务:嫩妹三件套 胸推👑 👑点评：御姐往少妇走的优质老师，天然d杯吊钟乳，颜值冷艳御姐，肥臀水多，逼烫人骚，人照8分，服务少，无毒龙，无舌吻，可惜了。服务一般，但长相身材，都符合顶御，故实名推荐！ https://t.me/cdlfls
❤1
Showing the 4 most recent of 4 posts we hold for @cdrblck. 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.
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.
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 14 August 2026 — this entry's latest reading, not the date you are reading this.
“日不落车库” (@cdrblck), 6,913 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/cdrblck.
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.