美团订餐记录最新一页➕酒店记录最新一页 美团订餐一页记录👍👍👍 美团订房一页记录👍👍👍 二个业务各一页一起打包👍👍👍👍 提供手机号出最新一页美团点餐记录加酒店 订房记录 纯美团内部直出 无遗漏 注:点餐只是记录 没有收货地址 加钱可以指定日期或出全部 只要下单了 当天的记录都能出 0延迟 订房记录比单开好(概率带同住人名字) 强推 业务咨询:@hmcd001 要素核验机器人:@hm110_bot

Channel
鸿蒙查档
@hmcd007
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
8,155subscribers
-361 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1004378014359 |
|---|---|
| Type | Channel |
| Username | @hmcd007 |
| Created | Between 1 June 2026 and 5 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 16 September 2026 |
| Measurements held | 13 |
| Confirmed unchanged | 1 time, most recently 16 September 2026 |
| On Telegram | t.me/hmcd007 |
Topic
Hacking & security — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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 |
|---|---|---|
| 16 Sept 2026, 22:39 | 8,155 | -6 |
| 12 Sept 2026, 19:55 | 8,161 | -29 |
| 8 Sept 2026, 10:15 | 8,190 | -31 |
| 2 Sept 2026, 18:15 | 8,221 | -56 |
| 30 Aug 2026, 18:57 | 8,277 | -156 |
| 27 Aug 2026, 09:42 | 8,433 | -15 |
| 24 Aug 2026, 08:35 | 8,448 | -1 |
| 20 Aug 2026, 13:21 | 8,449 | +10 |
| 17 Aug 2026, 12:52 | 8,439 | +10 |
| 14 Aug 2026, 01:29 | 8,429 | -22 |
| 10 Aug 2026, 17:02 | 8,451 | -65 |
| 7 Aug 2026, 18:34 | 8,516 | no change |
| 7 Aug 2026, 14:46 | 8,516 | first reading |
Engagement
21 posts held, back to 5 July 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 24 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.233%
- avg views ÷ 8,155 subscribers
- Avg views / post
- 19.0
- 1 post measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 1
- of 21 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 28 August 2026 |
|---|---|
| Posts held | 21 (5 July 2026 – 28 August 2026) |
| Views total | 19 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 28 Aug 2026, 17:30 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.
Reaction mix
1 reaction across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1 | 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 1 of the 21 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 1 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 5 July 2026 to 28 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.
Recent posts
小红书反电 👍👍👍 小概率旧绑 1-2天出 业务咨询:@hmcd001 要素核验机器人:@hm110_bot
车反电 开 👍👍 早了当天,晚了隔天 业务咨询:@hmcd001 要素核验机器人:@hm110_bot
🫣 建设银行流水 两年 300U 三年 360U 开卡 450U 1/3/5回单 业务咨询:@hmcd001 要素核验机器人:@hm110_bot
法人👍👍,人在就秒 业务咨询:@hmcd001 鸿蒙核验机器人:@hmhy110_bot
移动名下号 开 👍👍👍 无遗漏 业务咨询:@hmcd001 鸿蒙核验机器人:@hmhy110_bot
5年 医疗记录 👍👍👍 非发票改版 独家系统 和卫健委系统差不多数据 保真不保漏 全天人在秒 业务咨询:@hmcd001 要素核验机器人:@hm110_bot
12306 火车高铁半年记录 👍👍👍 (含未出行的订票信息➕同行人 ) 提供:大头手机号报单 当天回单 12306订票的高铁火车都出 无遗漏 业务咨询:@hmcd001 要素核验机器人:@hm110_bot
车辆大档 👍👍 业务咨询:@hmcd001 鸿蒙核验机器人:@hmhy110_bot
车管所名下车 开 👍👍👍 没车正常收费 业务咨询:@hmcd001
全面上线24小时 公网 真地址 人在就秒 业务咨询:@hmcd001
全面上线24小时 公网 真地址 人在就秒 业务咨询:@hmcd001
Showing the 12 most recent of 21 posts we hold for @hmcd007. 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.
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.
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@hmcd007 named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 23 posts, 8 August 2026 – 26 August 2026
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 16 September 2026 — this entry's latest reading, not the date you are reading this.
“鸿蒙查档” (@hmcd007), 8,155 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/hmcd007.
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.