#Cursor #开发者工具 Cursor IDE 的官方与社区开源插件 🌟 简介 Cursor 官方与开源社区打造的插件与扩展生态仓库,内含官方以及第三方的插件,有需要的群友可自行查看。 🔘 @TossLab 🔘 @TossLabChannel

Channel
折腾实验室频道
@TossLabChannel
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry
17,216subscribers
+995 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002441821742 |
|---|---|
| Type | Channel |
| Username | @TossLabChannel |
| Description | 📢群组: @TossLab 🎈频道: @TossLabChannel 青龙面板玩转自动化,Task签到任务收割乐趣,Docker容器装满脑洞,VPS服务器折腾到底,Github项目探秘新世界! 热爱折腾,永不停歇,爱折腾就来! |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 23 August 2026 |
| Measurements held | 17 |
| Confirmed unchanged | 1 time, most recently 23 August 2026 |
| On Telegram | t.me/TossLabChannel |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 23 Aug 2026, 20:44 | 17,216 | +72 |
| 22 Aug 2026, 06:47 | 17,144 | +49 |
| 20 Aug 2026, 23:59 | 17,095 | +34 |
| 20 Aug 2026, 02:03 | 17,061 | +30 |
| 18 Aug 2026, 23:42 | 17,031 | +27 |
| 17 Aug 2026, 20:55 | 17,004 | +112 |
| 16 Aug 2026, 20:54 | 16,892 | +413 |
| 15 Aug 2026, 10:57 | 16,479 | +50 |
| 13 Aug 2026, 23:28 | 16,429 | +28 |
| 12 Aug 2026, 16:36 | 16,401 | +36 |
| 11 Aug 2026, 16:16 | 16,365 | +32 |
| 10 Aug 2026, 18:21 | 16,333 | +31 |
| 9 Aug 2026, 21:52 | 16,302 | +28 |
| 8 Aug 2026, 23:04 | 16,274 | +17 |
| 8 Aug 2026, 00:51 | 16,257 | +17 |
| 7 Aug 2026, 01:51 | 16,240 | +19 |
| 6 Aug 2026, 04:07 | 16,221 | first reading |
Engagement
40 posts held, back to 1 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 37 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 16.8%
- avg views ÷ 17,216 subscribers
- Avg views / post
- 2,890
- 33 posts measured
- Reaction rate
- 0.085%
- reactions ÷ views · ER floor
- Posts in window
- 33
- of 40 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 28 of 33 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 24 August 2026 |
|---|---|
| Posts held | 40 (1 July 2026 – 24 August 2026) |
| Views total | 95,402 |
| Reactions total | 70 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 24 Aug 2026, 01:00 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
- 608
- Videos
- 17
- Links
- 673
Lifetime counters from Telegram’s own channel header, read 24 August 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.
Reaction mix
80 reactions across 29 posts, in 6 distinct kinds. The most used accounts for 65.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 52 | 65.0% | |
| 👍 | 21 | 26.3% | |
| 👏 | 3 | 3.75% | |
| 💩 | 2 | 2.50% | |
| 👎 | 1 | 1.25% | |
| 🥰 | 1 | 1.25% |
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 34 of the 40 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 82reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 40 most recent posts we hold, published 1 July 2026 to 24 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
#VirtualMacOniPad #iPad #macOS #虚拟机 #越狱 #AppleSilicon #M1 #M2 #iPadOS 🥲 让 iPad 直接运行 macOS VirtualMacOniPad 是一个开源项目,利用 Apple Silicon 虚拟化能力,让部分 M1/M2 iPad 越狱后运行 macOS,目前 GitHub 已获 1.4K+ Stars。 ⚡ 项目特点 · 支持 macOS 12~macOS 26 · 支持 Metal 图形加速 · 可运行 Xcode、Final Cut Pro 等 macOS 软件 · 基于硬件虚拟化,性能明显优于纯软件模拟 📱 使用要求 · M1/M2 iPad Pro、M1 iPad Air · iPadOS 14~16.3.1 · 必须越狱 ⚠️ iPadOS 16.4 及以上版本目前不支持,部分功能仍存在限制。 🔘@TossLab 🔘@TossL…
Signed Steven Lee
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_6787263594
Signed 极搜🔍资源搜索@JISOU
#频道互推 #群组推荐 不是白嫖,这叫借鉴(备用) 老司机之家 LSP游戏目录 Galgame|ADV|拔作|黄油 爱游戏分享社 JK精选 影视软件、TVBox接口分享 财联社VIP文章分享 独特吧-破解软件游戏资源分享 APP喵-软件资源共享 电报频道&群组索引
💩2
Signed 喵喵互推
#DeepSeek #Android #agent ⭐ DeepSeek (dsh) 安卓端启动器 🌟 简介 针对 Android 移动端打造的开源 DeepSeek / dsh 模型启动与管理工具。 📖 使用方法 下载安装后,配置页填入 DeepSeek API key,安装页点一键安装,等待安装即可。 🔘 @TossLab 🔘 @TossLabChannel
👍1
#罗技鼠标 #硬件外设 #效率工具 告别臃肿的开源轻量化罗技外设管理工具 🌟 简介 专为罗技鼠标与外设用户打造的 Logi Options+ 开源轻量级替代方案。摆脱官方驱动体积庞大、内存占用高和后台常驻进程繁琐的问题,还原极致纯粹的外设配置体验。 📖 核心功能 极致轻量无负担 按键与手势自定义 多平台原生兼容,无需注册或强制联网,即开即用 🔘 @TossLab 🔘 @TossLabChannel
👏3❤1
#金融 #同花顺 同花顺官方开源的金融数据 API 与智能体赋能套件 🌟 简介 同花顺官方开源的金融数据服务接口库,专为量化投研、数据分析及 AI Agent 场景打造。 📖 核心功能 全景市场行情覆盖 深度基本面与财报分析 Agent 即装即用 GitHub 链接 🔘 @TossLab 🔘 @TossLabChannel
👍3❤1
#信号处理 #科研工具 脉冲线性调频雷达信号处理与仿真工具库 🌟 简介 专注于线性调频雷达系统的全流程信号建模与仿真分析工具。覆盖从发射波形生成、多目标回波建模到脉冲压缩与多普勒测速的全套经典 DSP 处理流程,助力雷达算法快速验证与科研教学。 📖 核心功能 波形调制与参数定制:自由配置带宽、脉宽与 PRF 等核心参数,生成标准 LFM 脉冲波形 脉冲压缩与匹配滤波:内置时/频域匹配滤波与加窗算法,实现高信噪比与高距离分辨率 目标建模与 RD 谱图分析:支持多目标距离与速度多普勒解算,提供直观的距离-多普勒可视化 🔘 @TossLab 🔘 @TossLabChannel
DeepSeek-Harness插件导航站: https://findharness.com/
👍1
#GitHub项目 #劳动维权 #求职必备 Get My Fucking Money · 裁员应对卡 🌟 简介 针对职场维权痛点打造的劳动报酬与离职赔偿测算工具。非直接法律结论,它做的是帮你整理信息、准备沟通,并在合规边界内保留与本人权益相关的材料。 📖 部署方式 Codex skill/本地静态网页/Vercel 和 CF pages 🔘 @TossLab 🔘 @TossLabChannel
❤2
#编程 #java #python #C++ #NoSQL #热门项目 📱 Build Your Own X:教你从零手搓各种软件 GitHub 热门排行第一,已斩获 52w+ Star,这是一个专门教你从零造软件的教程合集。 🛠️ 能学什么? · 用 Java 打造自己的区块链 · 用 Python 做一个机器人 · 自己写一个 NoSQL 数据库 · 用 C++ 开发一款游戏 · 甚至还有操作系统、渲染引擎等项目 💡 核心思路 想真正搞懂一个东西,最好的办法就是自己动手造一个。 无论是编程新手,还是有经验的开发者,都能找到适合自己的项目练手。 🔘@TossLab 🔘@TossLabChannel
❤3
Signed Steven Lee
#AI #开源项目 #短视频 📱 10 万 Star 的开源 AI 短视频神器 MoneyPrinterTurbo 是一个开源的 AI 短视频生成工具。 🎬 输入主题,自动出片 · AI 生成脚本 · 自动配音、字幕 · 匹配视频素材 · 自动剪辑合成 几分钟即可生成完整短视频,适合 TikTok、Reels、YouTube Shorts 等平台。 💻 免费开源·本地部署 基于 Python + FFmpeg,可本地运行、自由修改。项目本身免费,但部分 AI 模型和素材服务需要自行配置 API。 适合 AI 短视频、批量出片、自媒体自动化。 🔘@TossLab 🔘@TossLabChannel
❤2
Signed Steven Lee
Showing the 12 most recent of 40 posts we hold for @TossLabChannel. 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.
Posts edited after publishing
@TossLabChannel edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
- First edit seen
- 18 August 2026
- Most recent edit
- 18 August 2026
Citation-graph rank
Citation-graph rank — 999,266 of 1,585,381entries 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 2 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 23 August 2026 — this entry's latest reading, not the date you are reading this.
“折腾实验室频道” (@TossLabChannel), 17,216 subscribers as measured 23 August 2026. Telegram Register, tgregister.com/channel/TossLabChannel.
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.