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Channel

Hermes爱马仕&🦞OpenClaw小龙虾

@openclaw1024

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

7,092subscribers

+310 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1003853389174
TypeChannel
Username@openclaw1024
Description分享Hermes爱马仕 & OpenClaw🦞最新玩法、技巧、经验、观点等。2026最新自主智能体(Agent)框架,你的24小时在线的“数字管家”。
CreatedBetween 1 February 2026 and 28 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live10 November 2026
Measurements held26
Confirmed unchanged1 time, most recently 10 November 2026
On Telegramt.me/openclaw1024

Topic

Technology — 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 the other topics.

Growth

6,7827,0926,9376 August 2026 — 6,782 subscribers6 August 2026 — 6,787 subscribers9 August 2026 — 6,796 subscribers13 August 2026 — 6,795 subscribers16 August 2026 — 6,810 subscribers19 August 2026 — 6,809 subscribers22 August 2026 — 6,814 subscribers26 August 2026 — 6,804 subscribers28 August 2026 — 6,811 subscribers1 September 2026 — 6,824 subscribers5 September 2026 — 6,871 subscribers10 September 2026 — 6,925 subscribers14 September 2026 — 6,956 subscribers18 September 2026 — 6,982 subscribers27 September 2026 — 7,002 subscribers5 October 2026 — 7,038 subscribers11 October 2026 — 7,049 subscribers15 October 2026 — 7,053 subscribers17 October 2026 — 7,063 subscribers20 October 2026 — 7,074 subscribers23 October 2026 — 7,082 subscribers26 October 2026 — 7,087 subscribers1 November 2026 — 7,076 subscribers4 November 2026 — 7,078 subscribers7 November 2026 — 7,081 subscribers10 November 2026 — 7,092 subscribers6 August 202610 November 2026
26 measurements spanning 97 days, net +310. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 6,736–7,139 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)SubscribersChange
10 Nov 2026, 16:497,092+11
7 Nov 2026, 00:157,081+3
4 Nov 2026, 04:577,078+2
1 Nov 2026, 05:587,076-11
26 Oct 2026, 13:467,087+5
23 Oct 2026, 13:507,082+8
20 Oct 2026, 07:007,074+11
17 Oct 2026, 16:457,063+10
15 Oct 2026, 00:387,053+4
11 Oct 2026, 22:387,049+11
5 Oct 2026, 15:197,038+36
27 Sept 2026, 19:587,002+20
18 Sept 2026, 12:556,982+26
14 Sept 2026, 07:216,956+31
10 Sept 2026, 10:386,925+54
5 Sept 2026, 10:376,871+47
1 Sept 2026, 10:186,824+13
28 Aug 2026, 23:366,811+7
26 Aug 2026, 02:426,804-10
22 Aug 2026, 23:086,814first reading

Engagement

73 posts held, back to 28 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 27 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
18.7%
avg views ÷ 7,092 subscribers
Avg views / post
1,330
27 posts measured
Reaction rate
0.203%
reactions ÷ views · ER floor
Posts in window
27
of 73 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 14 of 27 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 November 2026
Posts held73 (28 July 2026 – 10 November 2026)
Views total35,823
Reactions total38
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 02:56 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
724
Videos
208
Links
803

Lifetime counters from Telegram’s own channel header, read 11 November 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.

Video runtime
2m 34s
Average length
31s

Measured directly from 5 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.

Reaction mix

51 reactions across 18 posts, in 6 distinct kinds. The most used accounts for 54.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤2854.9%
👍1325.5%
👎713.7%
👌11.96%
😁11.96%
🫡11.96%

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 23 of the 73 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 51 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 73 most recent posts we hold, published 28 July 2026 to 10 November 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

Telegram’s own ‘edited’ marker: 0 of 27 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

10 Nov 2026, 19:08 UTC172 viewsread 11 November 2026
Video

Gemini Carbon 做的鹈鹕骑自行车演示,一个 Agent 负责构建,在 Blender 和 Three.js 上生成建模,一个 Agent 负责审查,检查它们自己的渲染结果,最终生成的可玩的 3D 游戏:一只鹈鹕骑着自行车在 Google 的 Mountain View 园区转悠。 测试地址:https://aistudio.google.com/apps/bundled/pelican-campus-quest?showAssistant=true&showPreview=true Hermes/OpenClaw | AI探索

10 Nov 2026, 10:49 UTC421 views4 reactionsread 11 November 2026

中日关系崩了,所有人都以为日本是在替美国冲锋、替台湾站台!错了!真相是:日本政府正在借着这股风浪,完成一场策划了几十年的“大国复活”手术。 把过去一年日本自己通过的文件、部署的装备和改掉的规则按时间排一排,会发现一个很整齐的节奏,外部关系越紧张,国内拆限制的动作就越顺。这不是被动站队,是借风使船。 最硬的一刀切在宪法上。2026年4月,高市早苗在自民党大会上,把修宪时间表摆上台面,自民党的方案很讲究,宪法第九条关于放弃战争、不保持战力的核心表述不动,在旁边新加一条,把自卫队写进去。 字面上和平宪法的承诺没改,实际上,自卫队从宪法没承认的东西,变成了宪法明文写出来的东西。自民党在众议院已有超过三分之二的修宪动议门槛,但参议院在野党反对强烈,前景并非板上钉钉。 可一旦走完,战后对日本军事力量的宪法约束,就在不碰敏感条文的掩护下被绕过去了。 钱的事比修宪更安静,也更实在。2026财年,防卫预算继续创新高,为了凑钱,日本开始从普通人身上…

❤4

8 Nov 2026, 06:43 UTC782 views7 reactionsread 11 November 2026
Photo

Claude pro明天开始涨价, 要的速来。 https://fang.aileaderme.top/categories/claude Hermes/OpenClaw | AI探索

👎6😁1

8 Nov 2026, 06:33 UTC754 views2 reactionsread 11 November 2026
Photo

Mnemos 是一个 Python 写的 MCP 服务器,把 agent 的记忆存在本机一个 SQLite 文件里,每个会开始时自动读回。 给 agent 十二个记忆工具,由 agent 自己用第一人称记下学到的东西、一起做出的决定和犯过的错误,每条记忆带有写入模型的签名。 记忆按遗忘曲线衰减,被回忆时增强并与同期召回的条目建立链接;淡到阈值时 agent 需要回答这条记忆教会了什么,答案作为更持久的经验留下。 https://github.com/Riley-Coyote/mnemos-mcp Hermes/OpenClaw | AI探索

❤2

7 Nov 2026, 01:16 UTC924 views2 reactionsread 11 November 2026

传统web developement需要云服务是刚需,因为必须有个物理机器host everything,需要一大堆组建和功能,像买盒饭一样从cloud service里买服务+付钱。 所以传统云服务等于勇哥称重自选快餐,等于一个赵一鸣,一定尽可能把标准化产品做成琳琅满目、种类齐全的一大堆非标品、排列组合卖给用户, 只有这样,里面才会夹杂价格刺客,才能把profit margin拉上来,才能让云厂商有利可图。 所以在传统云时代,AWS是唯一王者,因为一直在挖掘非标品的新需求,拉高溢价,才能成为大赢家,而所有卖三五个甚至一两个产品的人,想跟AWS竞争,要么只能打价格战,没有利润,要么自己做一个惊天动地的open source project,成为人人都用的infra,然后自己单独支个摊儿,卖自家的service。 agent sandbox的逻辑完全不同,因为天天开agent的人,需要sandbox完全只是需要一个ec2,租一个c…

❤1👍1

5 Nov 2026, 08:57 UTC≈1,160 views6 reactionsread 11 November 2026
Video

一位叫 富贵平安 网友做的视频,如果人生是一台电脑,在电脑里找到了那一晚的系统还原点,还能改变未来吗。 好有趣的视频,让我想起了蝴蝶效应,那种深深的无力感,如果救下她的代价是她的世界里再也没有你的位置,你还会救吗? 她的人生在没有我参与的情况下,才是最完美的。为了拯救你试了很多方法,但是我最后发现……只有远离你 才能让你平安 Hermes/OpenClaw | AI探索

👍6

4 Nov 2026, 03:53 UTC≈1,240 views1 reactionsread 11 November 2026

想搞懂 Claude Code 这类 AI Agent 内部怎么运转,NamiAgent 用一个能从 100 行跑起来的本地 Agent 课程从最小循环教到 MCP 与长期记忆。 https://github.com/aa1143/NamiAgent Hermes/OpenClaw | AI探索

🫡1

3 Nov 2026, 09:32 UTC≈1,320 viewsread 11 November 2026

手机也好、电脑也罢,所有的东西都存储在硬件里面,比如你手机12+256,那就是存在这个256里面。 你可以把它理解为一张白纸,不同设备存储、读取逻辑不同,但是也大相径庭。 存储就是你在这张自纸上写字,删除就是拿橡皮删除,恢复就是用一种显影液让删除的东西显现出来,然后根据不同的存储位置判断“它”属于什么。 Hermes/OpenClaw | AI探索

1 Nov 2026, 03:22 UTC≈1,600 views5 reactionsread 11 November 2026
Video

以防有人不知道!! 现在任何 Agent 都能直接装上Computer Use! Vercel Labs 正式开源了 agent-desktop,能给任何编程 Agent 加上桌面级的 Computer Use。 它和以前的做法不一样: 1、不靠截图!直接读系统的无障碍树,也就是界面上每个按钮、每个输入框的结构 2、在后台运行!不抢鼠标,你正常用电脑,它自己干它的! 3、几个 Agent 可以各用一个光标,同时干活! 4、支持macOS、Windows、Linux ! 上手很简单,一行命令安装:npm i -g agent-desktop Hermes/OpenClaw | AI探索

❤5

30 Oct 2026, 22:17 UTC≈1,430 viewsread 11 November 2026

哪个头部LLM公司、frontier lab、互联网厂投资wet lab大举进军搞生物制药大跃进,我都瞧不起他,有一个算一个。 一堆你妈靠算力和算法解决的大型工业仿真还没用agent一个个爆破,天天想着投钱造个wet lab爆破bioinfo的那点剩饭,属实是没出息。 党哥复读了无数次,再说一次,接下来36个月的趋势是让agent完成所有半导体的工作(cadence、synopsis)、仿真和控制(simulink、labview)、机械设计和航空航天船舶流体分析(ansys、CAD、abacus)。 这些问优先度,目前都要远远高于造个wet lab大规模几万个自动化设备养几百万个小白鼠培养皿柱子分析仪大规模并行几千个实验。 Hermes/OpenClaw | AI探索

30 Oct 2026, 22:10 UTC≈1,290 views4 reactionsread 11 November 2026
Photo

一个小技巧,很多公司的网页在线客服,默认都是那种 Q&A 的问答,就是默认一些选项让你选择,实际上得不到有效的回复,因为背后不是真人,这时候你可以试试输入“live agent”,那么会帮你转接真人客服。 Hermes/OpenClaw | AI探索

❤4

30 Oct 2026, 22:07 UTC≈1,040 viewsread 11 November 2026

哪个头部LLM公司、frontier lab、互联网厂投资wet lab大举进军搞生物制药大跃进,我都瞧不起他,有一个算一个。 一堆你妈靠算力和算法解决的大型工业仿真还没用agent一个个爆破,天天想着投钱造个wet lab爆破bioinfo的那点剩饭,属实是没出息。 党哥复读了无数次,再说一次,接下来36个月的趋势是让agent完成所有半导体的工作(cadence、synopsis)、仿真和控制(simulink、labview)、机械设计和航空航天船舶流体分析(ansys、CAD、abacus)。 这些问优先度,目前都要远远高于造个wet lab大规模几万个自动化设备养几百万个小白鼠培养皿柱子分析仪大规模并行几千个实验。 Hermes/OpenClaw | AI探索

Showing the 12 most recent of 73 posts we hold for @openclaw1024. 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 8 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.

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 10 November 2026 — this entry's latest reading, not the date you are reading this.

“Hermes爱马仕&🦞OpenClaw小龙虾” (@openclaw1024), 7,092 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/openclaw1024.

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.