Cloudflare 推出了钱包功能,现在可以免费认领自己的钱包了 似乎这个钱包是给Agent 用的 下了一盘大棋… 领取你的钱包:https://cloudflare.pay Hermes/OpenClaw | AI探索
Channel
Hermes爱马仕&🦞OpenClaw小龙虾
@openclaw1024
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
6,795subscribers
+13 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 |
|---|---|
| Type | Channel |
| Username | @openclaw1024 |
| Created | Between 1 February 2026 and 30 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/openclaw1024 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 00:35 | 6,795 | -1 |
| 9 Aug 2026, 17:51 | 6,796 | +9 |
| 6 Aug 2026, 23:42 | 6,787 | +5 |
| 6 Aug 2026, 03:47 | 6,782 | first reading |
Engagement
31 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 10 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 11.1%
- avg views ÷ 6,795 subscribers
- Avg views / post
- 754
- 31 posts measured
- Reaction rate
- 0.178%
- reactions ÷ views · ER floor
- Posts in window
- 31
- of 31 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 6 of 31 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 31 (28 July 2026 – 12 August 2026) |
| Views total | 23,365 |
| Reactions total | 12 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 02:46 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
- 1m 17s
- Average length
- 26s
Measured directly from 3 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
12 reactions across 6 posts, in 3 distinct kinds. The most used accounts for 83.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 10 | 83.3% | |
| 👌 | 1 | 8.33% | |
| 👎 | 1 | 8.33% |
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 6 of the 31 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 12reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 28 July 2026 to 12 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
腾讯做的这个团队记忆 Tencent Agent Memory 可以让团队里的多个 AI Agent 共享记忆 那多个 Agent 共用一份团队记忆后,如果写进去的是错误信息怎么办? Hermes/OpenClaw | AI探索
一年半以前感觉是刚需,今年连skills都懒得写,直接指示用playwright套个chrome自己解析google搜索结果了。 搜索这种白菜价甚至是土豆价的东西,这些厂商是哪里来的底气按次卖这么贵的。 Hermes/OpenClaw | AI探索
Cloudflare 钱包上线了! 据说是给agent用的,不管用不用的上,赛博菩萨的场得捧啊,先占个坑位!! 现在可以认领自己的专属handle! Hermes/OpenClaw | AI探索
Google 官方也搞 Agent Skills 仓库 了 把大量产品操作流程做成 Agent Skills 现在已经覆盖了 Google Ads、Gemini、GKE 等生产工具 不错不错😂 Hermes/OpenClaw | AI探索
DeepSeek-V4-Flash正式版刚上,Agent能力暴涨,便宜到离谱,1M上下文直接拉满。 正好配上DeepSeek-Reasonix:终端里跑的原生DeepSeek coding agent,单Go二进制,专为前缀缓存优化,长会token成本压得死死的。 配置驱动、插件随便插、多模型随便组合。 Hermes/OpenClaw | AI探索
我觉得像视频转录剪辑这样的 App 应该是被 Agent 调用的,App 主要是用来确认结果和微调的。 所以我在设计的时候,砍掉了内置的 Harness,只保留了复制 prompt,然后去 Agent 操作。另外最新版本提供了网页界面,这样可以在 Agent 内置浏览器内打开,直接从对或者网页标记二次编辑。 我坚信未来 Agent 才是入口,要做什么事是先打开 Agent 而不是打开 App。 Hermes/OpenClaw | AI探索
我说比较直,MiniMax H3比快乐马效果好多了! Hermes/OpenClaw | AI探索
卧槽,这哥们去霍霍 Codex 了吗?
这两天被刷屏的Mirasim, 是哪个无良团队搞出了的无耻玩意! 简直没有任何底线!虚假宣传!流氓软件!! 我今天早上安装的,还兴致勃勃分享了这个羊毛, 确实送了“所谓的会员”,但是tmd根本没有额度可用, 自家的会员都用不了,还有啥指望! 还阴梭梭的用我Codex的额度!! 然后一看,好家伙!简直劣迹斑斑!! 已经下载的朋友们,赶紧卸载,卸干净! 然后把这个软件、这个团队永远拉黑! Hermes/OpenClaw | AI探索
OpenAI 内部认为,3个月内Agent 会迎来一次新的使用范式。随着模型能力提升,单机运行很快触及瓶颈,未来一个 Agent 可能长期在线,同时处理大量任务,一台电脑已经难以支撑。 下一阶段需要云端大规模推理、多机协作、更完善的工具生态和长期记忆系统。 本质上,Agent 正从电脑里的一个程序,演变成一套持续运行的智能基础设施。 Hermes/OpenClaw | AI探索
很突然,学会了很多牛叉的技能!! 半夜一个人,一手抱着娃,另一只手冲奶粉、喂奶、等娃拉了给他洗屁股、再换尿不湿。 此时此刻,抱着娃一边哄睡,一边让Codex干活,有个方案明天ddl了,Codex必须加班干! Hermes/OpenClaw | AI探索
Showing the 12 most recent of 31 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.
Citation-graph rank
Citation-graph rank — 728,525 of 1,151,006entries 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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“Hermes爱马仕&🦞OpenClaw小龙虾” (@openclaw1024), 6,795 subscribers as measured 13 August 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.