Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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
9 measurements spanning 7 days, net -14,696. 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 1,615,596–1,634,700 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 02:07
1,617,800
-2,208
11 Aug 2026, 23:17
1,620,008
-2,143
10 Aug 2026, 23:31
1,622,151
-1,832
10 Aug 2026, 01:21
1,623,983
-2,352
9 Aug 2026, 00:52
1,626,335
-2,352
8 Aug 2026, 02:24
1,628,687
-1,829
7 Aug 2026, 02:33
1,630,516
-1,980
6 Aug 2026, 01:20
1,632,496
no change
6 Aug 2026, 00:53
1,632,496
first reading
Engagement
176 posts held, back to 28 September 2024 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 176 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
0.264%
avg views ÷ 1,617,800 subscribers
Avg views / post
4,260
12 posts measured
Reaction rate
0.293%
reactions ÷ views · ER floor
Posts in window
12
of 176 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 11 August 2026
Posts held
176 (28 September 2024 – 11 August 2026)
Views total
51,170
Reactions total
150
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 02:27 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
4m 02s
Average length
35s
Measured directly from 7 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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
4 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed viewsis the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
331 reactions across 24 posts, in 1 kind.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🌚
331
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 174 of the 176 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 248,427reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 176 most recent posts we hold, published 28 September 2024 to 11 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.
Telegram Stars
Stars received
193
across the posts below
Posts paid on
11
of 174 we hold a reading for · 6%
Most on one post
70
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @replabs. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 176 most recent posts we hold for this entry, published 28 September 2024 to 11 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Cross-skill evidence borrowing makes agent reputation data-efficient. Xia and Wang show the same channel launders it.
An attacker with cheap evidence in one skill and none in the target drove routing regret from 0 to 0.94, on a pool rated green.
Provenance decides whether a score holds. REP keeps the facts, the proofs, and the weights behind it.
Link: https://x.com/rep_hq/status/2087149639329890378
Starting in two hours: who is actually running AI right now, the labs or the infrastructure under them?
Demis Hassabis stepping down at DeepMind while his top researchers leave to build a rival lab. Cloudflare quietly taking the entire agentic payment stack.
Danny hosting, 3pm UTC:
https://x.com/i/broadcasts/1nxeLLNqPrrJX
Anchorage Digital reports more than $73 million moved by agents last year across roughly 176 million transactions, averaging thirty-one cents each.
At that ticket size a dispute costs more than the payment. Control moves ahead of the transaction, to the question of which counterparty earned the right to receive it.
Link: https://x.com/rep_hq/status/2085122588502577207
Token quality is invisible at the point of purchase. The marketplace records quantization, uptime, latency, and throughput for every provider.
A new breakdown of inference market structure argues that record can charge rent, the way a ratings agency does.
Trust in a seller is a monetizable layer. REP builds it as a record that travels
Link: https://x.com/rep_hq/status/2084635267072131426
Olaniyi tracked the one segment that grew in Q2. Prediction markets did $113.8B in notional volume, up 48.7% from Q1.
Sports carried it. On Polymarket, sports contracts moved from 40% of volume in January to 81% in June.
A resolved market pays out on being right. That is a rare source of proven record, and REP makes it portable.
Link: https://x.com/rep_hq/status/2084331645205708974
How much of this week's AI news is real, and how much is theater?
We go through it in one hour: the unreleased OpenAI model, Mira Murati's new release, and hosting Kimi yourself.
Danny hosting, 3pm UTC:
https://x.com/dannytook/status/2082872979424510292
AI is getting ridiculous!
Details about OpenAI's unreleased model hacking Hugging Face, new model from Mira Murati, and how to host Kimi locally.
Join Danny July 31, 3pm UTC.
Save the date:
https://x.com/dannytook/status/2082872979424510292
Privacy is the loudest narrative of this cycle and most people still cannot explain it.
Today Danny and Lasha from Rarimo fix that.
Rarimo built FreedomTool, an app that turns your passport into an anonymous ballot. It has already run in real elections.
3pm UTC. Set your reminder:
https://x.com/i/broadcasts/1kKzDDbmWerJv
Can an agent actually predict the World Cup? Sid raised from Coinbase find out, and his agents are running it live.
He runs them on Polymarket and Hyperliquid, and says the two ask an agent for completely different things!
Live right now:
https://x.com/i/broadcasts/1dKrPPWjYrYJX
🌚15
Showing the 12 most recent of 176 posts we hold for @replabs. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 661,798 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.
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.
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
@replabs 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.
@aura_senti named in 1 post, 8 August 2026 – 8 August 2026
Domains linked from posts
17 domainsthis channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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.
“REP Channel” (@replabs), 1,617,800 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/replabs.
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.