Github Top Repositories
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Top GitHub repositories in one place π Explore the best projects in programming, AI, data science, and more.
Show moreπ Analytical overview of Telegram channel Github Top Repositories
Channel Github Top Repositories (@githubre) in the English language segment is an active participant. Currently, the community unites 14 214 subscribers, ranking 13 963 in the Education category and 28 251 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 14 214 subscribers.
According to the latest data from 30 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 288 over the last 30 days and by 45 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.02%. Within the first 24 hours after publication, content typically collects 0.67% reactions from the total number of subscribers.
- Post reach: On average, each post receives 145 views. Within the first day, a publication typically gains 95 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
- Thematic interests: Content is focused on key topics such as repository, fork, programming, statistic, description.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βTop GitHub repositories in one place π
Explore the best projects in programming, AI, data science, and more.β
Thanks to the high frequency of updates (latest data received on 31 August, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
14 214
Subscribers
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+677 days
+28830 days
Posts Archive
14 214
π Meet mattpocock/skills: a gem from today's GitHub trending list.
π https://github.com/mattpocock/skills
π Skills for Real Engineers. Straight from my .claude directory.
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Unlock Efficient Software Development with the GitHub repo "mattpocock/skills". This collection of skills is designed to help real engineers develop applications efficiently, tackling common failure modes in software development.
The key features of this repo include grilling sessions to align with the agent, a shared language to reduce verbosity, and feedback loops to ensure the code works as expected.
To get started, simply run the
skills.sh installer and pick the skills you want to use. You can also install the skills as a Claude Code plugin for a plug-and-play experience.
These skills are perfect for developers and engineers looking to streamline their workflow and develop high-quality applications. With mattpocock/skills, you can focus on writing great code and leave the tedious tasks to the agent.
In short, mattpocock/skills helps you build better software, faster.
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π§ Channel: https://t.me/GithubRe14 214
π Meet HKUDS/DeepTutor: a gem from today's GitHub trending list.
π https://github.com/HKUDS/DeepTutor
π DeepTutor: Lifelong Personalized Tutoring.https://deeptutor.info/.
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DeepTutor: Lifelong Personalized Tutoring is an innovative platform that offers a personalized learning experience. Its key features include a chat agent loop, multimodal image extraction, and support for multiple languages. To get started, simply visit the
deeptutor.info website and follow the instructions. The platform is built using Python 3.11+ and Next.js 16, and is licensed under the Apache 2.0 license.
The platform is designed for students, educators, and researchers who want to create a personalized learning experience. It offers a range of technical highlights, including support for multiple AI models, a knowledge graph, and a customizable interface. The platform also has a strong community of contributors and users, who can be reached through Discord, Feishu, and WeChat.
Overall, DeepTutor is a powerful tool for anyone looking to create a personalized learning experience. With its user-friendly interface and advanced features, it's an ideal choice for anyone looking to take their learning to the next level. Get started with DeepTutor today and discover a new way of learning!
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π§ Channel: https://t.me/GithubRe
14 214
π Spotted on GitHub Trending: YimMenu/YimMenuV2 β let's break it down.
π https://github.com/YimMenu/YimMenuV2
π Experimental menu for GTA 5: Enhanced
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The YimMenuV2 GitHub repository is a C++20 mod menu base project, created as a personal learning experience. Its template-heavy approach aims to provide a foundation for mod menus. The project is structured into three main directories:
core for essential features, game for game-specific implementations, and util for miscellaneous functions. This base is ideal for developers looking to explore C++20 and mod menu development. It's a work in progress, with a core, game, and util structure that's easy to navigate. The takeaway: template your way to mod menu mastery with YimMenuV2.
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π§ Channel: https://t.me/GithubRe14 214
π Deep-diving into lobehub/lobehub β fresh off the trending list.
π https://github.com/lobehub/lobehub
π π€― LobeHub is your Chief Agent Operator, organizing your agents into 7Γ24 operations by hiring, scheduling, and reporting on your entire AI team.
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LobeHub is a cutting-edge platform that revolutionizes the way you work with AI agents. Its purpose is to organize your agents into a 24/7 operation, allowing you to hire, schedule, and report on your entire AI team. The key features include Agent Builder, Unified Intelligence, and
10,000+ Skills to connect your agents to the tools you use every day.
To get started, you can self-host LobeHub using Vercel, Docker, or Alibaba Cloud, making it easy to deploy and manage your AI team. The platform also allows for Collaboration and Co-evolution of humans and agents, enabling parallel collaboration and iterative improvement.
LobeHub is ideal for developers and users looking to streamline their AI workflow. With its open-source nature and active community, you can provide feedback and contribute to its development.
In a nutshell, LobeHub is your one-stop-shop for AI agent management - it's like having your own AI team, minus the hassle!
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π§ Channel: https://t.me/GithubRe
14 214
π― Shubhamsaboo/awesome-llm-apps landed on trending. Worth a proper look.
π https://github.com/Shubhamsaboo/awesome-llm-apps
π 100+ AI Agent & RAG apps you can actually run β clone, customize, ship.
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The Shubhamsaboo/awesome-llm-apps GitHub repository is a treasure trove of 100+ open-source AI agents, agent skills, and RAG apps that can be easily cloned and customized. With a focus on
Apache-2.0 licensed projects, this repository offers a wide range of applications, from agent skills that can be added to existing coding agents to starter AI agents that can be run with just an API key. The repository also features advanced AI agents with tools, memory, and multi-step reasoning, as well as always-on agents that run on schedules or events. Whether you're a developer looking to build on top of these projects or a user looking to explore the possibilities of AI, this repository has something for everyone. Get started with a new skill in 10 seconds using npx skills add https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/agent_skills/project-graveyard and discover the power of AI agents for yourself. With new templates dropping weekly, the possibilities are endless - clone, customize, and create your own AI agent today!
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π§ Channel: https://t.me/GithubRe
14 214
π₯ hasaneyldrm/exercises-dataset is trending β and it deserves your attention.
π https://github.com/hasaneyldrm/exercises-dataset
π 1,324-exercise fitness dataset β animation GIFs, 180Γ180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
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The hasaneyldrm/exercises-dataset repository is a treasure trove of fitness enthusiasts, containing a comprehensive dataset of 1,324 exercises with detailed metadata, including
category, body-part, equipment, target and muscle-group data. Each exercise comes with an animation GIF and a 180Γ180 thumbnail image, along with step-by-step instructions in 10 languages. The dataset is perfect for building fitness or workout planning applications, machine learning projects, health and wellness research, and educational demonstrations.
To get started, you can explore the interactive index.html browser, which allows you to filter exercises by category, equipment, and target muscle. The setup.html guide provides a step-by-step tutorial on integrating the dataset into your own application, including database setup and API integration.
Whether you're a developer, researcher, or fitness enthusiast, this dataset has something to offer. So, dive in and start exploring the world of exercises!
Takeaway: With the hasaneyldrm/exercises-dataset, you can power your fitness applications and take your workout planning to the next level!
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π§ Channel: https://t.me/GithubRe
14 214
π Spotted on GitHub Trending: PrismML-Eng/Bonsai-demo β let's break it down.
π https://github.com/PrismML-Eng/Bonsai-demo
π Bonsai Demo
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The Bonsai-demo repository provides a local demo for running Bonsai and Ternary-Bonsai language models on various platforms, including Mac, Linux, Windows, and CPU. The repository features vision-language models that accept images and text, as well as agentic tool calling and reasoning models.
To get started, users can run the
./setup.sh command to download the required models and binaries, and then use the ./scripts/start_llama_server.sh command to start the demo server. The repository supports different model sizes, including 27B, 8B, 4B, and 1.7B, and allows users to switch between the Ternary and 1-bit families.
The demo is suitable for developers and researchers interested in natural language processing and computer vision. With its tiny footprint and support for long context conversations, the Bonsai-demo is an exciting project that showcases the potential of efficient language models.
One-liner takeaway: Experience the power of efficient language models with the Bonsai-demo, where you can run vision-language models locally and explore the possibilities of agentic tool calling and reasoning models.
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π§ Channel: https://t.me/GithubRe14 214
π Deep-diving into openinterpreter/openinterpreter β fresh off the trending list.
π https://github.com/openinterpreter/openinterpreter
π A coding agent for low-cost models
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The Open Interpreter is a coding agent that shines with low-cost models. Key features include a harness emulation system that gets the most out of these models, a
/harness command to switch between different harnesses, and a built-in QA skill for testing web and native apps.
To get started, simply run a curl or irm command to install, then type i or interpreter to start a session. The project has a strong focus on documentation, with guides covering everything from installation to configuration and CLI references.
With its robust set of features, including native sandboxing, provider switching, and local config storage, Open Interpreter is perfect for developers and power users looking to streamline their workflow.
Embracing the power of open-source and community-driven development, Open Interpreter is licensed under Apache-2.0 and has a thriving community around it.
Takeaway: Open Interpreter is an ultra-versatile coding agent that's redefining the limits of low-cost models, one line of code at a time.
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π§ Channel: https://t.me/GithubRe14 214
π Meet PostHog/posthog: a gem from today's GitHub trending list.
π https://github.com/PostHog/posthog
π π¦ PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, data warehouse, a CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack.
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PostHog is an all-in-one, open source platform for building successful products, providing a wide range of tools to understand user behavior and analyze data. Its key features include product analytics, web analytics, session replays, feature flags, experiments, and error tracking. To get started, you can sign up for
PostHog Cloud or self-host the open-source version using Docker. The platform offers a generous monthly free tier and has a vast range of SDKs and libraries for popular languages and frameworks. Whether you're a product manager, developer, or engineer, PostHog is designed to help you build better products and drive growth. So, why wait? Join the PostHog community today and start building a better product tomorrow!
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π§ Channel: https://t.me/GithubRe14 214
π₯ OpenCut-app/OpenCut is trending β and it deserves your attention.
π https://github.com/OpenCut-app/OpenCut
π The open-source CapCut alternative
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OpenCut is a free and open source video editor for web, desktop, and mobile. It's currently being rewritten from the ground up with exciting new features like an Editor API, first-class third party plugins, and a plugin-first architecture. The new version will have a
Rust core and offer desktop, mobile, and browser support from one codebase. Other features include an MCP server for AI agents, headless mode for automation and batch rendering, and a scripting tab directly in the editor.
To get started with development, you can install proto and run the application in web:dev, api:dev, or desktop:dev modes. The project is still in the process of being designed, but you can join the Discord or open an issue to follow along and ask questions.
OpenCut is supported by companies that believe in open source creator tools, such as fal.ai. The project is licensed under MIT.
One-liner takeaway: OpenCut is revolutionizing video editing with its open source, plugin-first approach, and soon you'll be able to experience the future of video editing for free.
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π§ Channel: https://t.me/GithubRe14 214
π― Nutlope/hallmark landed on trending. Worth a proper look.
π https://github.com/Nutlope/hallmark
π Anti-AI-slop design skill for Claude Code, Cursor, and Codex.
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Hallmark is a design skill that generates unique, AI-produced web pages that don't look like they were made by a machine. With twenty themes and a range of customization options, Hallmark uses a set of design rules to create self-contained HTML + CSS pages. The skill has four main verbs: build, audit, redesign, and study, allowing users to
hallmark build, hallmark audit <target>, hallmark redesign <target>, or hallmark study <screenshot | URL>. Hallmark is designed for use with Claude Code, Cursor, and Codex, and can be installed using npx skills add nutlope/hallmark. The result is a unique, human-like design that refuses to be bound by typical AI-generated templates. With Hallmark, every brief gets a unique design - no two pages are alike! One-liner takeaway: Hallmark is the AI design skill that breaks the mold of boring, cookie-cutter templates.
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π§ Channel: https://t.me/GithubRe
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π₯ apache/ossie is trending β and it deserves your attention.
π https://github.com/apache/ossie
π Apache Ossie, industry wide specification effort to standardize how we exchange semantic metadata across analytics, AI and BI platforms, providing a vendor neutral, single source of truth for semantic data
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Apache Ossie is a collaborative effort to standardize semantic model exchange and utilization across data analytics, AI, and BI tools. The goal is to establish a vendor-agnostic semantic model specification for unparalleled interoperability and efficiency. This project provides a single JSON- and YAML-based specification that tools can read and write, addressing semantic fragmentation.
Key features include a
core-spec for the Ossie specification, converters for translating between Ossie and other formats, and examples of semantic models. The project also offers tooling for validation against the Ossie schema.
Audience: data analysts, AI professionals, and BI practitioners seeking to streamline their workflows. To get involved, contribute code, participate in discussions, or join the Slack community.
Here's a glimpse of the code:
{
"spec": "ossie-spec"
}14 214
π hasaneyldrm/exercises-dataset caught my eye on GitHub Trending today.
π https://github.com/hasaneyldrm/exercises-dataset
π 1,324-exercise fitness dataset β animation GIFs, 180Γ180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
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The exercises-dataset repository, created by hasaneyldrm, is a comprehensive collection of 1,324 fitness exercises, each with an animation GIF, 180Γ180 thumbnail image, category, body-part, equipment, target and muscle-group data, and step-by-step instructions in 9 languages. The dataset is designed for building fitness or workout planning applications, machine learning projects, health and wellness research, and educational demonstrations.
Key features of the dataset include:
- 1,324 exercises with detailed metadata
- Animation GIFs and thumbnails for each exercise
- Step-by-step instructions in 9 languages
- Interactive browser for easy exploration of exercises
The dataset is
MIT licensed, with additional media terms. It powers the LogPress app, an AI-assisted workout tracker, and can be easily integrated into other applications.
The dataset is suitable for developers, researchers, and fitness enthusiasts looking to build or enhance their fitness-related projects.
One-liner takeaway: With the exercises-dataset, you can supercharge your fitness app with a vast, high-quality collection of exercises and metadata.
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π§ Channel: https://t.me/GithubRe14 214
β‘ YimMenu/YimMenuV2 is making waves. Here's the full picture.
π https://github.com/YimMenu/YimMenuV2
π Experimental menu for GTA 5: Enhanced
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The YimMenuV2 repository is a C++20 mod menu base that serves as a learning opportunity for its creator. The project's structure is divided into three main directories:
core/ for essential features, game/ for game-specific implementations, and util/ for general utility functions. This base is designed to provide a foundation for modding, with a focus on templating and experimentation. It's geared towards developers looking to explore C++20 and mod menu development. The takeaway: Learning by doing is the best way to template your way to mod menu mastery!
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π§ Channel: https://t.me/GithubRe