Channel
@kxcr002
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
776subscribers
+2 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003917917780 |
|---|---|
| Type | Channel |
| Username | @kxcr002 |
| Created | Between 1 April 2026 and 26 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 1 time, most recently 7 August 2026 |
| On Telegram | t.me/kxcr002 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 18:55 | 776 | +2 |
| 7 Aug 2026, 06:17 | 774 | first reading |
9 posts held, back to 26 June 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.
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.
| Window | Rolling 30 days · latest post in window 2 August 2026 |
|---|---|
| Posts held | 9 (26 June 2026 – 2 August 2026) |
| Views total | 10,390 |
| Reactions total | 9 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 06:17 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.
21 reactions across 8 posts, in 2 distinct kinds. The most used accounts for 90.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 19 | 90.5% | |
| 👍 | 2 | 9.52% |
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 9 of the 9 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 21reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 26 June 2026 to 2 August 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.
#棉花糖 @Mht19 6/10 八月初的深夜已经浸了薄凉，十一点的街道只剩路灯拖着昏黄的长影，巷口的风卷着梧桐叶擦过裤脚，我按响门铃的时候，指尖还沾着晚风里的草木气。 门开的瞬间，暖黄的灯光漫出来。她穿一件素白抹胸，配着洗得发软的浅蓝色牛仔裤，长发松松垂在肩后，鹅蛋脸上只扫了淡妆，眉眼乖得像学生时代邻班的女生，是越看越耐看的模样。 沙发很软，我们隔着一臂的距离聊天。她比想象中健谈太多，说话的时候喜欢用手轻轻比划，抹胸的边缘随着动作偶尔提起一截，露出肚脐上那枚小小的钉，冷光一闪，又藏回去。我夸她好看，她歪着头笑，说“别逗了”，声音有点沙，大概是刚抽过烟。问她抽什么，她说炫赫门。我愣了一下，忍不住笑出声——没想到她也爱这个。她从茶几下面摸出烟盒，细支，蓝绿色包装，在我眼前晃了晃：“甜嘴的，戒不掉。” 后来我们也聊了别的，不过主要是我在吐槽生活中的事儿，很多都是没法向熟悉…
❤1
#琳琳 @lin17840 7/12 六点的晚风裹着楼下香樟的味道钻进楼道时，我指尖还留着刚按过门铃的微麻感。门拉开的瞬间先撞进一双弯起来的眼睛，琳琳软软的长发垂在肩头，发梢扫过黑色情趣套装滑腻的面料，深壑的事业线随着她侧身让我进来的动作轻轻晃了晃，脸颊上的薄妆带了点若有似无的卡粉感，乖得像常在便利店碰到的邻家女孩，谁能想到门后是一场提前约好的暮色春宵呢。 沙发的海绵软得陷进去半个身子，她健谈的语气像杯温温的蜜水，从最近追的剧扯到楼下新开的甜品店，小腿不经意蹭过我的时候，带着点健身练出来的紧实暖意，163的个子一百斤的肉全长得恰到好处，没有多余的赘余，手搭在沙发边缘的时候，胳膊上还藏着点浅浅的肌肉线条，干干净净看不到纹身的痕迹，连指甲都修剪得十分可爱。 热气腾腾的水流从花洒淌下来的时候，瓷砖上蒙了层薄雾，两个人的皮肤贴着彼此蹭过沐浴露的泡沫，指腹擦过她腰上紧致的腰线，连水…
❤1
#允茉 @yunmoai 7/12 门铃响过三声，她来开门。绿衫轻薄，两根细带挂在肩上，锁骨窝里盛着一小片阴影。一袭长发，耳垂上缀一颗很小的珍珠。她比照片里瘦，手臂上那几处淡青色纹样，像被雨水洇开的墨痕。 我们坐在沙发上聊天。沙发很软，坐下去便陷出一个恰好的弧度。她盘着腿，腿上处露出一小截藤蔓似的刺青。聊天时她总微微侧着头，偶尔伸手把散落的发丝别到耳后。笑声明亮，不是我想象中那种疏离的御姐模样。 灯光偏暖，照见她鼻翼有一点卡粉的痕迹，像晨雾没有散尽。她的嘴唇厚而柔软，说话时缓慢张合，像浸过水的花瓣。后来我们接吻，证实了那个猜想——真的很软，带着薄荷烟清冽的余味，仿佛舌尖碰到的是一片微凉的晚风。 后来的事情像一场恰到好处的雨。她回应得自然投入，手指攥紧又松开的瞬间，我看见她闭上眼睛，睫毛微颤，空气里漫着淡淡的汗意与烟草味。原来亲密可以这样抵达——不是占有，而是彼此确认的存在。…
❤2
#优优 @youyou521001 6/10 晚上七点整，我准时敲响了妹妹家的门。优优今年二十岁，身高大概一米六，体重一百斤左右，身材匀称得恰到好处。肩膀锁骨下的纹身在灯光下若隐若现，像一抹秘密的印记。她不抽烟，身上只有淡淡的沐浴露香。今天她特意穿了JK制服，配着超短裙，白皙的大腿几乎全露在外面，走路时裙摆轻轻晃动，性感得要命。淡妆化得有点卡粉，却更显出那张乖巧的脸，再加上那副眼镜，活脱脱一位眼镜娘，又纯又欲。 刚进门我们就坐在沙发上聊天。话没说几句，她就主动靠近，跨坐在我大腿上。那一刻我哪里还是什么正人君子，立刻搂住她不算纤细，略有肉感的腰，低头吻了上去。妹妹的嘴巴甜甜的，舌头软得像棉花糖，我们激烈地交缠，津液拉丝，啧啧作响。我的手从她短裙下探进去，摸到光滑的大腿根，再往上就是温热的骚逼，隔着内裤都能感觉到湿意。她身子瞬间软了下来，软得像一滩春水，靠在我怀里轻轻喘息，眼镜片上起了…
❤3👍2
#沁颜 @qinyan111 7/12 午后三点的阳光刚好斜落在她家米色沙发上。她开门时白色衬衣的领口微敞，包臀裙勾勒出的线条在逆光里显得格外分明。淡妆，远看精致，近了些才发现粉底在鼻翼两侧有细微的斑驳——这让她酷似舒淇的长相多了一层烟火气。 她健谈，从之前的工作聊到最近追的剧，边说边用指尖捻着一支细长的烟。我注意到她胳膊外侧有一小片墨色，像是蝴蝶的翅膀藏在袖口里。烟雾在她脸前散开时，那些不完美都成了某种生动的注脚。 后来事情就那样发生了。她比我想象中投入，手指穿过我头发时带着轻微的颤抖，像在弹一架走音却依然温柔的钢琴。黑丝在匆忙中勾了丝，她没在意，只是把脸埋进枕头里闷声笑。窗外有车鸣笛，在这个闷热的下午显得格外遥远。 事后我靠在床头点了根烟，她也重新燃了一支。我们聊起各自童年养过的宠物，她讲起那只走丢的橘猫时眼眶微红，烟灰落在床单上也没察觉。时间在烟雾里走得特别快，等我掐灭烟头…
#知画 @zhihuabb 6/11 七月十四，夜，闷热。 约好八点，到她家楼下时，我抬头看了一眼那扇亮着灯的窗。门开，黑色连衣裙先映入眼，衬得她本就偏瘦的身形愈发单薄。她化了淡妆，眉眼清秀，神情却冷冷的，像一只绷着弦的野猫——黑皮，骨感，带着点拒人千里的模样。可那双眼睛出卖了她，躲闪，游移，不敢与我对视太久。 沙发上坐下，起初几句寒暄还有些涩。烟盒搁在茶几上，她顺手摸出一根，动作熟稔地点上，烟雾模糊了她脸侧的轮廓。话匣子却渐渐打开了。她讲话意外地坦诚，甚至有点絮叨，讲到开心处会下意识看我一眼，确认我的反应，再飞快移开目光。那是一种小心翼翼的讨好，像在试探水温。我忽然就看见了盔甲底下那个害羞的、总觉得自己不够好的小姑娘。心里某处被轻轻撞了一下——太像了，像几年前那个拼命用外壳包裹软肋的自己。 后来灯熄了。黑暗里她反而松弛下来，指尖微凉，呼吸轻而急促，像一只终于肯收起刺的刺猬，笨拙地、…
❤2
【花名】#成都圣德堡控射训练 【车牌】@cd7772 【价格】套餐A 698/套餐B 798 【验证】开心超人 【评分】8 【硬件】客服未让我选人，随机开技师盲盒，来者脸6分左右，年龄大概30，162，105，胸B+，乳晕中等，豆豆突出，下面未进行观测 【软件】按摩，胸推，舌尖漫游，各种手法控射，射后抓龙筋保养 【体验】 很久没来过抓龙筋了，最近也想体验一下。联系客服后，客服只发了菜单和地址，我看客服频道里则只有些客人的评价，没有任何技师的照片，我也没问，这种真正按摩保养的其实手法比颜值更重要，就只接开盲盒了。 来到教室，技师就普通长相，身材偏微胖，腿看着很有力气。她贴心的给我倒水和拿来拖鞋，稍微聊了后我独自去洗浴，出来她前后都给我擦了，擦得很仔细。 接着开始服务，我首先趴在床上，她就货真价值的给我按摩，小腿、屁股、背部、脖子，不是装模做样那种，是真的用力在按，把我痛得精叫唤。从下到上按摩完之后，她拉下上衣，开始胸推，舌尖也…
❤4
【花名】#Cici 【车牌】@ci66880 【价格】7P/11PP 【验证】开心超人 【评分】8.5 【硬件】重庆妹妹，芳龄24，人照9，与频道黑色旗袍照基本一致，真人苹果机略微有点突出，脸有点卡粉，典型的御姐，身高160，体重85左右，胸C，略微有点外八乳，乳晕较大，乳头凸出，屁屁有肉，黄皮，胸口左乳上方有个小纹身，逼型为蝴蝶，毛量偏多，阴唇为褐色，掰开后粉嫩，进入后小鸡有包裹感； 【软件】三件套，耳语+阴推等课表内容 【体验】 今天天气实在炎热，其实不是很想出击，无奈锅锅的任务来了，我也是老任务达人了，那还是果断出门。来到一个第一次来的小区，环境略微有点破旧，心情也略微有点烦躁。 在代的指引下进门，心情一下畅快了，一眼就看到一位身材娇小的御姐，但突出的胸部曲线实在有些夸张，和她的身躯形成强烈的反差，让人移不开眼睛。我在沙发上坐下，Cici贴心为我拿来了矿泉水和拖鞋，我们就这样开始闲聊，屋内的空气虽然冷，但好像我们之间的温…
❤3
#粽子 @zz116688z 7/12 #报成都学院写报告减1 下午两点，敲开那扇门的时候，手心竟有些汗津津的。 门开处，一袭蓝色马面裙先映入眼，裙裾的褶子层层叠叠，走动时如水波微漾。她抬起头来，淡妆下的眉眼间有几分紧张，唇角微微抿着，透出些故作镇定的冷清。可那圆润的苹果肌和忽闪的睫毛，又分明是个甜妹的模样。 起初坐在沙发上，两个人中间隔着半臂的距离，空气里飘着若有若无的香水味。她说话倒是爽利，一口软糯的西南官话听着让人心里熨帖。聊着聊着，这姑娘的话匣子就跟开了闸似的，从老家山里的野果说到刚买的汉服，又从汉服说到下个月的工资要怎么花。她说这话时眼睛亮晶晶的，手也不闲着，比划着新买的裙子有多好看。 我看着她，忽然觉得这世上最动人的风景，大概就是这样鲜活的生命力罢。 后来，许是话说得尽了，许是午后太过安静，我们渐渐靠近。她低下头时，额前的碎发扫过我的下巴，痒痒的。马面裙的系带不知何…
❤3
Showing the 9 most recent of 9 posts we hold for @kxcr002. 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 — 170,798 of 1,350,102entries 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.
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 3 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.
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 7 August 2026 — this entry's latest reading, not the date you are reading this.
“祝你天天开心” (@kxcr002), 776 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/kxcr002.
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.