Channel
@githubtrending
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
11,693subscribers
+506 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001080389054 |
|---|---|
| Type | Channel |
| Username | @githubtrending |
| Created | 27 November 2016 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 6 August 2026 |
| Last confirmed live | 4 October 2026 |
| Measurements held | 36 |
| Confirmed unchanged | 1 time, most recently 4 October 2026 |
| On Telegram | t.me/githubtrending |
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 11 September 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 4 Oct 2026, 14:00 | 11,693 | +71 |
| 26 Sept 2026, 04:16 | 11,622 | +86 |
| 17 Sept 2026, 12:59 | 11,536 | +25 |
| 15 Sept 2026, 08:42 | 11,511 | +12 |
| 13 Sept 2026, 16:56 | 11,499 | +7 |
| 12 Sept 2026, 00:58 | 11,492 | +31 |
| 9 Sept 2026, 15:38 | 11,461 | +9 |
| 6 Sept 2026, 07:58 | 11,452 | +20 |
| 4 Sept 2026, 04:15 | 11,432 | +10 |
| 2 Sept 2026, 18:16 | 11,422 | +14 |
| 1 Sept 2026, 16:48 | 11,408 | +9 |
| 31 Aug 2026, 14:24 | 11,399 | +10 |
| 30 Aug 2026, 11:55 | 11,389 | +19 |
| 29 Aug 2026, 09:55 | 11,370 | +7 |
| 28 Aug 2026, 12:14 | 11,363 | +14 |
| 27 Aug 2026, 13:54 | 11,349 | +13 |
| 26 Aug 2026, 14:54 | 11,336 | +8 |
| 25 Aug 2026, 11:53 | 11,328 | -1 |
| 24 Aug 2026, 13:15 | 11,329 | +29 |
| 22 Aug 2026, 18:58 | 11,300 | first reading |
87 posts held, back to 29 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 43 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 87 posts for this entry, the most recent from 2 September 2026. An engagement rate over an empty window would be a number about nothing.
98 reactions across 54 posts, in 7 distinct kinds. The most used accounts for 56.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 55 | 56.1% | |
| ❤ | 24 | 24.5% | |
| ⚡ | 6 | 6.12% | |
| 👌 | 5 | 5.10% | |
| 👎 | 4 | 4.08% | |
| 🎉 | 2 | 2.04% | |
| 🔥 | 2 | 2.04% |
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 60 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 99 reactions 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 29 July 2026 to 2 September 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.
#rust #ai #ai_coding_assistant #claude_code #codex #coding_agents #git #gitops #kilo_code #mcp #mcp_client #opencode #opencode_ai #opencode_skills #self_hosted #skills Atlas is a local app for coding agents that records what each agent did, why it did it, and what code changed. It lets you use tools like Claude Code and Codex together, share memory between them, and keep your code, notes, and sessions on your own ma…
❤1
#typescript Portless gives each local app a simple name like https://myapp.localhost instead of a hard-to-remember port number. It starts your dev server through a proxy, turns on HTTPS by default, and can handle monorepos, worktrees, LAN sharing, and public sharing with Tailscale or ngrok. This makes local development easier because URLs stay stable, safer because HTTPS works automatically, and faster because you d…
👍2❤1
#python #agent_skills #ai_writing #claude_code #codex #cursor #prompt_engineering #writing_tools Humanizer rewrites AI-like text so it sounds more natural and human while keeping the meaning the same. It checks for common AI writing patterns, avoids inventing facts, can match your writing style, and leaves code, data, and links unchanged. The benefit to you is cleaner text that reads better and feels more real, with…
👍1👎1
#python #bge #colbert #data_pipeline #deep_learning #embeddings #inference #inference_server #information_retrieval #llm #ml #mlops #natural_language_processing #nlp #python #reranking #retrieval #retrieval_augmented_generation #semantic_search #splade #vector_search SIE is a self-hosted engine for AI agents that runs many open models from one cluster in your cloud. It can handle search, document cleanup, structured…
👍1👎1
#python #ai #audiobook #cuda #dubbing #elevenlabs_alternative #huggingface #local_first #mlx #omnivoice_studio #speech_to_text #tauri #text_to_speech #transcription #translate #tts #voice_ai #voice_cloning #voice_generation #voicestudio #workflow VoiceStudio is a local app for voice cloning, dubbing, dictation, and long audio work on macOS, Windows, and Linux. It works offline after setup, keeps your voices and file…
👌2
#typescript #ai #ai_agent #ai_tools #cli #coding OpenClaude is a terminal app for coding with AI. It works with many cloud and local models, supports tools, agents, slash commands, streaming, and saved provider profiles. This helps you use one simple workflow instead of switching between different AI tools, and it can speed up coding, debugging, and long tasks. https://github.com/Gitlawb/openclaude
👎1
#html ReClip is a self-hosted, open-source tool that lets you paste links from many sites and download videos as MP4 or audio as MP3. It has a simple web page, supports bulk downloads and quality choice, and runs locally, so it can save time and make downloading media easier for you. https://github.com/averygan/reclip
🎉1
#python #automation #bot #clarifai #instagram #python #script #selenium This project is about using AI and Python tools to automate social media tasks like likes, comments, and followers. The main benefit for you is learning practical automation ideas, tools, and examples that can save time and help you build your own bots, but it also warns that heavy use can lead to bans. https://github.com/InstaPy/InstaPy
👌2❤1👍1🔥1
#java #code_quality #command_line_tool #hacktoberfest #java #static_analysis #static_code_analysis Checkstyle is a Java tool that finds code style and best-practice problems, so you can catch mistakes early and keep code clean. It is easy to add to your build, has docs and examples, and helps you spot issues like a switch-case fall-through before they cause bugs, making your code safer and easier to maintain. https…
👍3👌1
#python #chinese #disclosure #obsidian #patent #skill This tool helps you turn project files into clear patent drafts for invention, utility model, and design patents, and it can also explain patents in simple words. It can find patent points, make charts and Word files, build line drawings, organize patent notes, and help with search, policy updates, and office reply drafts. The benefit to you is faster patent work…
#swift vphone-cli lets you create and run a virtual iPhone on a Mac with Apple Silicon and macOS 15 or later. It can download firmware, patch it, restore it, install a custom system, and boot the phone with one command. This helps you test iPhone software, use SSH or VNC, and manage or clone virtual phones easily. https://github.com/Lakr233/vphone-cli
👍1
#python Microduck RL gives training environments for a small biped robot, so you can teach it walking, standing up, sitting, tricks, and roller tasks in simulation, then export the learned policy to run on the real robot. It includes realistic motor physics, backlash, and random changes to help sim-to-real transfer. The benefit to you is faster robot training, easier testing, and safer deployment because one shared …
👍2
Showing the 12 most recent of 87 posts we hold for @githubtrending. 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.
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.
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.
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.
This channel appears in 8 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 4 October 2026 — this entry's latest reading, not the date you are reading this.
“GitHub Trends” (@githubtrending), 11,693 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/githubtrending.
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.