browser-use/macos-harness The simplest, thinnest harness that gives an LLM complete freedom to control a Mac. Language: Python #accessibility #agent #automation #cdp #computer_use #macos #python Stars: 696 Issues: 6 Forks: 45 https://github.com/browser-use/macos-harness

Channel
GitHub repos
@github_repos
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
26,999subscribers
+143 since we began measuring on 5 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001065452260 |
|---|---|
| Type | Channel |
| Username | @github_repos |
| Description | Welcome to GitHub repos. Here you'll find valuable information on the latest trending projects. Subscribe to stay informed and gain insights from the thriving GitHub community. |
| Created | 1 July 2016 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 21 August 2026 |
| Measurements held | 17 |
| Confirmed unchanged | 1 time, most recently 21 August 2026 |
| On Telegram | t.me/github_repos |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 21 Aug 2026, 10:48 | 26,999 | -2 |
| 20 Aug 2026, 12:18 | 27,001 | +12 |
| 19 Aug 2026, 11:35 | 26,989 | +14 |
| 18 Aug 2026, 14:33 | 26,975 | +9 |
| 17 Aug 2026, 11:24 | 26,966 | +1 |
| 15 Aug 2026, 20:24 | 26,965 | +20 |
| 14 Aug 2026, 07:16 | 26,945 | +17 |
| 13 Aug 2026, 00:24 | 26,928 | +9 |
| 12 Aug 2026, 02:02 | 26,919 | +22 |
| 11 Aug 2026, 04:25 | 26,897 | +8 |
| 10 Aug 2026, 01:14 | 26,889 | +13 |
| 9 Aug 2026, 00:50 | 26,876 | +1 |
| 8 Aug 2026, 02:34 | 26,875 | +10 |
| 7 Aug 2026, 00:33 | 26,865 | +5 |
| 6 Aug 2026, 03:40 | 26,860 | +4 |
| 6 Aug 2026, 02:01 | 26,856 | no change |
| 5 Aug 2026, 23:03 | 26,856 | first reading |
Engagement
87 posts held, back to 1 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 35 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 3.65%
- avg views ÷ 26,999 subscribers
- Avg views / post
- 985
- 87 posts measured
- Reaction rate
- 0.199%
- reactions ÷ views · ER floor
- Posts in window
- 87
- of 87 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 39 of 87 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 22 August 2026 |
|---|---|
| Posts held | 87 (1 August 2026 – 22 August 2026) |
| Views total | 85,717 |
| Reactions total | 76 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 22 Aug 2026, 18:59 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
- ≈18
- Videos
- ≈2
- Links
- ≈12,800
Lifetime counters from Telegram’s own channel header, read 22 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Reaction mix
72 reactions across 33 posts, in 12 distinct kinds. The most used accounts for 38.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 28 | 38.9% | |
| 🔥 | 22 | 30.6% | |
| 🎉 | 6 | 8.33% | |
| 👌 | 4 | 5.56% | |
| 💩 | 4 | 5.56% | |
| 💯 | 2 | 2.78% | |
| 👍 | 1 | 1.39% | |
| 👎 | 1 | 1.39% | |
| 👏 | 1 | 1.39% | |
| 🙏 | 1 | 1.39% | |
| 🤡 | 1 | 1.39% | |
| 🤷 | 1 | 1.39% |
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 39 of the 87 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 76reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 87 most recent posts we hold, published 1 August 2026 to 22 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
MengTo/threeui Open-source ThreeUI Community catalog with live interactive components and complete Community source. Language: HTML #react #shaders #threejs #ui_components #webgl Stars: 832 Issues: 1 Forks: 85 https://github.com/MengTo/threeui
❤2
Alain00/blobatar Language: TypeScript Stars: 620 Issues: 3 Forks: 38 https://github.com/Alain00/blobatar
SigmanticAI/apex-inference-chip An inference chip design that runs a real LLM (Qwen2.5-0.5B) on FPGA — one transformer decoder layer in RTL, every silicon value bit-exact against a golden model. 0.56 tok/s measured, a 140× climb, full evidence trail. Language: Python Stars: 647 Issues: 0 Forks: 1 https://github.com/SigmanticAI/apex-inference-chip
DenisSergeevitch/desktop-fly A 3D fruit fly living on your macOS desktop, driven by a live spiking simulation of the real FlyWire connectome Language: Swift Stars: 649 Issues: 5 Forks: 38 https://github.com/DenisSergeevitch/desktop-fly
❤2👎1🤷1
Leutenegger/vanity-eth Offline vanity address generator for Bitcoin and Ethereum. CPU multi-process search with interactive CLI menu. Supports Legacy, Nested SegWit, Native SegWit, Taproot, and ETH (EIP-55). Language: Python Stars: 801 Issues: 0 Forks: 90 https://github.com/Leutenegger/vanity-eth
🎉1
vvxw/deploy-vercel Install Command:npm install Language: JavaScript Stars: 597 Issues: 2 Forks: 117 https://github.com/vvxw/deploy-vercel
🔥1
vibeinging/deepseek-harness-desktop-app DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts. Language: JavaScript #agentic_workflows #ai_agent #ai_workbench #data_analysis #deepseek_harness #desktop_app #dsh #dsh_plugin #electron #local_first #mcp #model_context_protocol #office_automation #react #typescript Stars: 604 Issues: 6 For…
CopilotKit/openbot Open-source AI coworkers that each get a computer of their own: a browser, files and tools, with every action decided before it happens and recorded after. Bring any AG-UI agent. Language: TypeScript #ag_ui #agent_governance #ai_agents #browser_automation #copilotkit #generative_ui #mcp Stars: 854 Issues: 21 Forks: 79 https://github.com/CopilotKit/openbot
👏1
Leutenegger/watermarks-remover Remove multi-vendor AI provenance traces: Unicode text sanitization, statistical rewriting techniques, and C2PA/metadata stripping from PNG/JPEG/SVG/PDF/DOCX/HTML/MD files Language: Python #claude #claude_code #claude_skills #codex #codex_cli #codex_desktop #codex_plugin #codex_skill #codex_skills #grok #grok_45 #grok_ai #grok_build #grok_cli #watermark #watermark_detection #watermark_t…
🔥3
Larryvrh/ComfyUI-MiniMax-H3-Turbo Language: Python Stars: 418 Issues: 16 Forks: 27 https://github.com/Larryvrh/ComfyUI-MiniMax-H3-Turbo
❤1
NanmiCoder/dsh-agent-teams AgentTeams plugin for DeepSeek Harness Language: TypeScript #agentteams #deepseekharness #dsh #dsh_agent_teams #dsh_plugin Stars: 582 Issues: 19 Forks: 55 https://github.com/NanmiCoder/dsh-agent-teams
Showing the 12 most recent of 87 posts we hold for @github_repos. 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 — 742,451 of 1,584,142entries 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
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
@linuxgram · 72,798
Telegram ranks this channel #11 of 90 here — alongside 89 others — read 19 August 2026
@computer_science_and_programming · 140,868
Telegram ranks this channel #13 of 87 here — alongside 86 others — read 13 August 2026
@codeslearningTG · 270,922
Telegram ranks this channel #30 of 84 here — alongside 83 others — read 11 August 2026
@Curious_Coder · 136,420
Telegram ranks this channel #54 of 75 here — alongside 74 others — read 13 August 2026
@goyalarsh · 194,130
Telegram ranks this channel #66 of 69 here — alongside 68 others — read 11 August 2026
@gocareers · 79,803
Telegram ranks this channel #68 of 77 here — alongside 76 others — read 18 August 2026
@Artificial_intelligence_in · 65,539
Telegram ranks this channel #69 of 90 here — alongside 89 others — read 21 August 2026
@internfreak · 58,630
Telegram ranks this channel #71 of 82 here — alongside 81 others — read 22 August 2026
@jobs_and_internships_updates · 199,470
Telegram ranks this channel #81 of 82 here — alongside 81 others — read 11 August 2026
@placementkit · 133,851
Telegram ranks this channel #82 of 92 here — alongside 91 others — read 13 August 2026
This channel appears in 10 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 21 August 2026 — this entry's latest reading, not the date you are reading this.
“GitHub repos” (@github_repos), 26,999 subscribers as measured 21 August 2026. Telegram Register, tgregister.com/channel/github_repos.
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.