报告模板 反馈报告 上课时间:8.27 验证留名:哆啦咪哦 所在位置:东城 老师名称:许如烟 @xuruyany 上课价格:600 妹子年龄:22 妹子容貌:9.5 妹子身材:10 服务态度:10 环境设备:10 自由评论:身材高挑,该有肉的地方都有哈,老师很爱干净,浴巾一次性还有素口水,口活确实可以,一边口一边看着你的眼睛,特别享受,同时还用手撩摸着我的大腿内侧感觉酥酥麻麻,服务不多,但是正常该有的都有,换了四个姿势一顿输出,舒舒一遍一遍叫着爸爸,叫床的声音很真实,下面很紧致,我说你是不是在夹,她说没有啊,直接给我下面包裹住又紧又会夹直接射了,不太会写报告哈哈,颜控身材控的来 狼友群 https://t.me/DG760

Channel
许如烟
@xuruyanyan
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
1,474subscribers
+218 since we began measuring on 27 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
Register entry
| Telegram ID | -1002035557082 |
|---|---|
| Type | Channel |
| Username | @xuruyanyan |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 27 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 8 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/xuruyanyan |
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 17 September 2026 and assigned it the closest of 31 fixed categories, at 49% 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 |
|---|---|---|
| 17 Sept 2026, 13:39 | 1,474 | +35 |
| 13 Sept 2026, 21:37 | 1,439 | +32 |
| 10 Sept 2026, 14:21 | 1,407 | +26 |
| 5 Sept 2026, 16:40 | 1,381 | +30 |
| 2 Sept 2026, 00:16 | 1,351 | +39 |
| 30 Aug 2026, 09:44 | 1,312 | +38 |
| 27 Aug 2026, 18:56 | 1,274 | +18 |
| 27 Aug 2026, 15:30 | 1,256 | first reading |
Engagement
20 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 1 page of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 18.0%
- avg views ÷ 1,474 subscribers
- Avg views / post
- 265
- 8 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 8
- of 20 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.
| Window | Rolling 30 days · latest post in window 27 August 2026 |
|---|---|
| Posts held | 20 (5 August 2026 – 27 August 2026) |
| Views total | 2,123 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 27 Aug 2026, 15:30 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
- Video runtime
- 35s
- Average length
- 9s
Measured directly from 4 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
人是会变的 简单的五个字 讲完了
是不是肾虚没力气 回个信息那么费劲的
听说有钱人也会不开心 我想体验下
我很乖的
我很懒,也没啥特长但爱你是一把好手
东莞98每一份报告都来自群友,基本都带转发来源,除非群友不愿意直接转发,坚决不做收好处费假报告✊ 98群报告模板: 上课时间:8.20 验证留名:沙盒上 所在位置:东城 老师名称:许如烟# 老师电报:@xuruyany 上课价格:600 妹子年龄:22 总体评分(满分10分): 容貌评分: 10 身材评分: 9 服务评分: 9 环境评分: 9 自由评论: 该有的都有 一进门就看见老师躲在门后 身高和身材都非常的nice 洗完澡老师就带着我去挑选好看的制服黑丝 全程聊天感受都很好 喷射完老师还想用嘴给我弄一下 不行了 扛不住了 东莞避坑交流(老师🈲入): https://telegram.me/+m8dh0w7pgNphNzRl 更多资源👉👉👉: @DG98JTbot 提交报告: @FB128858bot
不知道你有没一瞬间 也会想起我
营月中 约起来
今日宜接收偏爱
装作漫不经心 目光却总偏向你
表面漫不经心 ,心里早已反复回想
Showing the 12 most recent of 20 posts we hold for @xuruyanyan. 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
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 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.
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“许如烟” (@xuruyanyan), 1,474 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/xuruyanyan.
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.