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Github Top Repositories
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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Показати більше📈 Аналітичний огляд Telegram-каналу Github Top Repositories
Канал Github Top Repositories (@githubre) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 13 260 підписників, посідаючи 15 384 місце в категорії Освіта та 32 523 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 13 260 підписників.
За останніми даними від 09 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 373, а за останні 24 години на 13, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 1.17%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.73% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 155 переглядів. Протягом першої доби публікація в середньому набирає 97 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 1.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як repository, fork, programming, statistic, description.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Завдяки високій частоті оновлень (останні дані отримано 10 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.
13 260
Підписники
+1324 години
+737 днів
+37330 день
Архів дописів
13 260
🚀 Meet addyosmani/agent-skills: a gem from today's GitHub trending list.
🔗 https://github.com/addyosmani/agent-skills
📝 Production-grade engineering skills for AI coding agents.
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Boost your coding game with the
agent-skills repository, a collection of 21 production-grade engineering skills for AI coding agents. These skills cover the entire development lifecycle, from /spec to /ship, and include tasks like test-driven development, code review, and security hardening. With seven slash commands, you can easily activate the right skills for your project. The repository also includes pre-configured agent personas and reference checklists to help you get started. Whether you're using Claude Code, Cursor, or Gemini CLI, agent-skills has got you covered. Take your coding to the next level with this powerful tool - Code smarter, not harder.
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🧠 Channel: https://t.me/GithubRe13 260
🌟 Lordog/dive-into-llms caught my eye on GitHub Trending today.
🔗 https://github.com/Lordog/dive-into-llms
📝 《动手学大模型Dive into LLMs》系列编程实践教程
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The Lordog/dive-into-llms GitHub repository is a hands-on programming tutorial series for getting started with large language models (LLMs). The project, also known as "动手学大模型", aims to provide a free and open-source resource for students and researchers to quickly learn and deploy LLMs.
The tutorial series covers a range of topics, including
微调与部署 (model fine-tuning and deployment), 提示学习与思维链 (prompt learning and thought chain), 知识编辑 (knowledge editing), 数学推理 (mathematical reasoning), and more.
The repository also includes a new series of tutorials, 大模型开发全流程 (the full process of large model development), developed in collaboration with Huawei's Ascend community. This series provides a comprehensive guide to developing and deploying LLMs, covering topics such as model development, optimization, and safety.
The project welcomes contributions and issues discussions, and its contributors include researchers and students from Shanghai Jiao Tong University and the National University of Singapore.
Whether you're a beginner or an experienced researcher, this repository has something to offer. So, dive into LLMs and start exploring the world of large language models - your next AI project is just a git clone away!
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🧠 Channel: https://t.me/GithubRe13 260
🔥 playcanvas/supersplat is trending — and it deserves your attention.
🔗 https://github.com/playcanvas/supersplat
📝 3D Gaussian Splat Editor
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The SuperSplat Editor is a free, open-source tool for creating and editing 3D Gaussian Splats. This web-based application allows users to inspect, optimize, and publish their splats without any downloads or installations. Key features include a live version available at https://superspl.at/editor, a user guide for learning, and a local development environment for contributors. To get started with local development, clone the repository and run
npm install followed by npm run develop.
git clone https://github.com/playcanvas/supersplat.git
cd supersplat
npm install
npm run develop
13 260
🔍 Deep-diving into masterking32/MasterDnsVPN — fresh off the trending list.
🔗 https://github.com/masterking32/MasterDnsVPN
📝 Advanced DNS tunneling VPN for censorship bypass, optimized beyond DNSTT and SlipStream with low-overhead ARQ, resolver load balancing, high packet-loss stability and speed.
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README not available for this repository.
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🧠 Channel: https://t.me/GithubRe
13 260
⚡ ChromeDevTools/chrome-devtools-mcp is making waves. Here's the full picture.
🔗 https://github.com/ChromeDevTools/chrome-devtools-mcp
📝 Chrome DevTools for coding agents
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The Chrome DevTools for Agents (
chrome-devtools-mcp) repository provides a Model-Context-Protocol (MCP) server that enables coding agents to control and inspect a live Chrome browser. Key features include performance insights, advanced browser debugging, and reliable automation.
To use chrome-devtools-mcp, you'll need Node.js and Chrome installed. The repository provides a CLI for use without MCP. You can configure your MCP client to use the server by adding the provided config.
The server supports various MCP clients, including Gemini, Claude, Copilot, and Cursor. It also provides a slim mode for basic browser tasks.
Technical highlights include the use of puppeteer for automation and Chrome DevTools for performance insights. The server also sends usage statistics to Google by default, which can be disabled.
The target audience for this repository includes developers and users of coding agents who want to leverage the power of Chrome DevTools for automation, debugging, and performance analysis.
In short, chrome-devtools-mcp empowers your coding agent to supercharge your development workflow with the full power of Chrome DevTools - automate, debug, and optimize your way to better coding.
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🧠 Channel: https://t.me/GithubRe13 260
🌟 rowboatlabs/rowboat caught my eye on GitHub Trending today.
🔗 https://github.com/rowboatlabs/rowboat
📝 Open-source AI coworker, with memory
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Rowboat is an open-source AI coworker that helps you get work done by turning your work into a knowledge graph and acting on it. It connects to your email and meeting notes, builds a long-lived knowledge graph, and uses that context to assist you in various tasks. You can use
Rowboat to generate decks, prep for meetings, track people or topics, and visualize your knowledge graph.
The tool is local-first, meaning all your data is stored locally as plain Markdown, giving you full control over your information. Rowboat also supports integrations with various tools and services, including Gmail, Google Calendar, and Composio.
Whether you're looking to boost your productivity or simply want a more organized workflow, Rowboat is definitely worth checking out. Here's a glimpse of what you can do with Rowboat in Python:
import rowboat
# Connect to your email and meeting notes
rowboat.connect_to_email()
rowboat.connect_to_meeting_notes()
# Generate a deck about your next quarter roadmap
rowboat.generate_deck("Next Quarter Roadmap")
13 260
⚡ datawhalechina/easy-vibe is making waves. Here's the full picture.
🔗 https://github.com/datawhalechina/easy-vibe
📝 💻 vibe coding 2026 | Your first modern programming course for beginners to master step by step.
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The datawhalechina/easy-vibe GitHub repository is a treasure trove for anyone looking to dive into the world of coding and AI development. Its primary purpose is to provide a beginner-friendly learning platform where users can turn their ideas into real products by conversing with AI. The key features include a step-by-step visual tutorial, immersive simulated coding, and visible AI principles.
To get started, users can simply describe what they want, and the platform will guide them through the process. The repository offers various learning paths tailored to different needs, including a fast first win, turning an idea into a product prototype, building full-stack products, and advancing Claude Code and agent workflows.
Technical highlights of the repository include interactive demos, cross-platform project tutorials, and a comprehensive knowledge base covering computer fundamentals, AI principles, and engineering practices.
The platform is designed for a wide range of audiences, from complete beginners to mid-level and senior developers, as well as product managers and founders.
In short,
datawhalechina/easy-vibe is your one-stop-shop for learning AI-assisted coding, and with its interactive approach, you can turn your ideas into products in no time. So, what are you waiting for? Dive into the world of Easy-Vibe and start building your dream projects today - if you can talk, you can build apps!
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🧠 Channel: https://t.me/GithubRe
13 260
💡 datawhalechina/hello-agents just hit the trending charts — here's why it matters.
🔗 https://github.com/datawhalechina/hello-agents
📝 📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
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Hello-Agents is a comprehensive open-source project that aims to provide a systematic guide to building intelligent agents from scratch. The project is designed for AI developers, software engineers, and students who want to gain a deep understanding of intelligent agents and their applications.
The project covers a wide range of topics, including the basics of intelligent agents, language models, and their applications. It provides a
step-by-step guide on how to build intelligent agents, from the basics to advanced topics such as memory and retrieval, context engineering, and agent training.
One of the key features of Hello-Agents is its emphasis on practical implementation. The project provides a fully executable codebase that allows users to implement and experiment with intelligent agents. The codebase is written in Python and is designed to be easy to understand and modify.
The project also includes a range of real-world examples and case studies that demonstrate the application of intelligent agents in various domains. These examples include travel assistants, research agents, and social simulation agents.
Overall, Hello-Agents is a valuable resource for anyone interested in building intelligent agents and gaining a deep understanding of the underlying technologies. With its comprehensive coverage of topics, practical implementation, and real-world examples, it is an ideal project for researchers, developers, and students alike.
Start building your own intelligent agents today and join the Hello-Agents community to learn from and contribute to this exciting project!
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🧠 Channel: https://t.me/GithubRe
13 260
🌟 rohitg00/agentmemory caught my eye on GitHub Trending today.
🔗 https://github.com/rohitg00/agentmemory
📝 #1 Persistent memory for AI coding agents based on real-world benchmarks
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The agentmemory GitHub repository provides a persistent memory solution for AI coding agents, allowing them to recall previous interactions and maintain context. The key features of agentmemory include auto-capture of interactions, retrieval accuracy of 95.2%, and support for multiple agents through MCP and REST API.
To use
npx @agentmemory/agentmemory, simply run the command, and the agent will start capturing interactions and maintaining context. This eliminates the need for re-explaining previous interactions, making it a valuable tool for developers.
The technical highlights of agentmemory include its use of BM25, vector, and graph search algorithms, as well as its support for leases, signals, and SQLite storage. The repository also includes benchmarks and comparisons with other competitors, demonstrating the effectiveness of agentmemory.
agentmemory is designed for developers who work with AI coding agents, particularly those who use Claude Code, Cursor, Gemini CLI, Codex CLI, and other MCP clients. With its easy-to-use interface and robust features, agentmemory is an essential tool for anyone looking to improve their productivity and efficiency when working with AI coding agents.
In summary, agentmemory is a game-changer for AI coding agents, providing persistent memory and recall capabilities that make development faster and more efficient - with agentmemory, your coding agent remembers everything, so you don't have to.
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🧠 Channel: https://t.me/GithubRe
13 260
🔍 Deep-diving into bytedance/UI-TARS-desktop — fresh off the trending list.
🔗 https://github.com/bytedance/UI-TARS-desktop
📝 The Open-Source Multimodal AI Agent Stack: Connecting Cutting-Edge AI Models and Agent Infra
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The UI-TARS-desktop GitHub repository offers a powerful desktop application that leverages the UI-TARS model to provide a native GUI Agent. This application is part of the TARS* multimodal AI Agent stack, which includes Agent TARS and UI-TARS-desktop. Agent TARS brings the power of GUI Agent and Vision into your terminal, computer, browser, and product, primarily shipping with a CLI and Web UI for usage.
Key features of Agent TARS include a one-click out-of-the-box
CLI, hybrid browser agent, event stream, and MCP integration. The UI-TARS-desktop application provides a desktop GUI Agent based on the UI-TARS model, supporting local and remote computer operators, as well as browser operators.
To get started with Agent TARS, you can launch it with npx @agent-tars/cli@latest or install it globally with npm install @agent-tars/cli@latest -g. For more information, you can visit the comprehensive Quick Start guide.
UI-TARS-desktop is designed for users looking for a seamless and intelligent desktop experience, while Agent TARS is ideal for developers and power users who want to leverage the power of multimodal AI Agents.
In a nutshell, UI-TARS-desktop and Agent TARS are revolutionizing the way we interact with our computers and browsers, making it more human-like and efficient - experience the future of AI-powered desktop applications today!
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🧠 Channel: https://t.me/GithubRe
13 260
🔥 anthropics/financial-services is trending — and it deserves your attention.
🔗 https://github.com/anthropics/financial-services
📝 No description.
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The Claude for Financial Services GitHub repository provides a comprehensive set of tools and templates for financial services workflows, including investment banking, equity research, private equity, and wealth management. The repository offers reference agents, skills, and data connectors that can be installed as
Claude Cowork plugins or deployed via the Claude Managed Agents API.
Key features include:
- Agents: named, end-to-end workflow agents (e.g., Pitch Agent, Market Researcher) that can be installed and tuned to a firm's specific needs
- Vertical plugins: skill and command bundles for specific financial services verticals (e.g., investment banking, equity research)
- Data connectors: integrations with various data providers (e.g., Daloopa, Morningstar, S&P Global) via the Model Context Protocol (MCP)
To get started, users can install the repository as a Claude Cowork plugin or deploy it via the Claude Managed Agents API. The repository also includes a Claude for Microsoft 365 install tool for provisioning the Claude add-in in a customized Microsoft 365 environment.
The target audience for this repository includes financial services professionals, developers, and IT administrators looking to automate and streamline their workflows using AI-powered tools.
In short, the Claude for Financial Services repository is a powerful toolkit for financial services firms looking to leverage AI and automation to boost productivity and efficiency - and the best part is, it's all customizable to how your firm works.
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🧠 Channel: https://t.me/GithubRe13 260
🌟 Augani/openreel-video caught my eye on GitHub Trending today.
🔗 https://github.com/Augani/openreel-video
📝 OpenReel Video - Professional browser-based video editor. Open source CapCut alternative. 100% browser-based, no installation, no cloud uploads, no watermarks.
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OpenReel Video is a free, open-source, browser-based video editor that runs entirely client-side, offering professional-grade video editing without the need for expensive software or cloud processing. With key features like a multi-track timeline, keyframe animations, color grading, and audio effects, it's an alternative to popular video editing software.
Try it live at openreel.video or run it locally by cloning the repository and installing dependencies.
The editor is built with React, TypeScript, WebCodecs, and WebGPU for smooth 4K editing and fast exports. It's suitable for anyone looking for a free, user-friendly, and feature-rich video editing solution.
Takeaway: OpenReel Video is revolutionizing video editing by making it free, open-source, and accessible to everyone, forever.
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🧠 Channel: https://t.me/GithubRe13 260
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