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 15 216 підписників, посідаючи 13 409 місце в категорії Освіта та 26 085 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 15 216 підписників.
За останніми даними від 05 листопада, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 393, а за останні 24 години на 6, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 0.92%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.62% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 140 переглядів. Протягом першої доби публікація в середньому набирає 95 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 06 листопада, 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.
15 216
Підписники
+624 години
+837 днів
+39330 днів
Архів дописів
15 221
🚀 Meet anthropics/claude-code: a gem from today's GitHub trending list.
🔗 https://github.com/anthropics/claude-code
📝 Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.
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Meet Claude Code, a cutting-edge coding tool that simplifies your development workflow. It understands your codebase, executes routine tasks, explains complex code, and handles git workflows using natural language commands. You can use it in your terminal, IDE, or even tag @claude on Github.
Key features include seamless integration, customization with plugins, and a user-friendly interface. To get started, simply install Claude Code using one of the recommended methods, such as
curl -fsSL https://claude.ai/install.sh | bash for MacOS/Linux, and run claude in your project directory.
Technical highlights of Claude Code include its ability to learn from your codebase and adapt to your workflow, making it an invaluable tool for developers of all levels. Whether you're a seasoned pro or just starting out, Claude Code is designed to help you code faster and more efficiently.
The target audience for Claude Code is developers who want to streamline their workflow, improve productivity, and focus on the creative aspects of coding. With its extensive documentation and community support, including a Discord channel and GitHub issues, you'll never be left in the dark.
In short, Claude Code is a game-changer for developers - it's like having a personal coding assistant at your fingertips. Get ready to revolutionize your coding experience with Claude Code: code smarter, not harder.
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🧠 Channel: https://t.me/GithubRe
15 221
🔍 Deep-diving into twentyhq/twenty — fresh off the trending list.
🔗 https://github.com/twentyhq/twenty
📝 The open alternative to Salesforce, designed for AI.
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The Twenty open-source CRM is designed for technical teams, providing a customizable foundation to meet complex business needs. It allows you to build, ship, and version your CRM like any other part of your tech stack.
Key features include
defineObject for defining custom objects, FieldType for specifying field types, and a CLI for scaffolding new apps and publishing them to your workspace.
To get started, you can sign up for the cloud version, build an app using the Twenty CLI, or self-host using Docker Compose. The project is built with a tech stack that includes TypeScript, Nx, NestJS, React, and more.
The Twenty CRM offers a range of tools and features, including objects, views, workflows, and agents, as well as version control and layouts. It's designed to be extensible and customizable, with a strong focus on community involvement and open-source development.
Whether you're a developer, contributor, or user, Twenty has something to offer. So why not join the community, star the repo, and start building your own custom CRM today? With Twenty, you can create the CRM you need, without being held back by the CRM you have.
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🧠 Channel: https://t.me/GithubRe15 221
🔍 Deep-diving into EveryInc/compound-engineering-plugin — fresh off the trending list.
🔗 https://github.com/EveryInc/compound-engineering-plugin
📝 Official Compound Engineering plugin for Claude Code, Codex, Cursor, and more
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The Compound Engineering plugin is designed to make each unit of engineering work easier than the last by inverting traditional development's accumulation of technical debt. With a focus on planning, review, and codifying knowledge, this plugin provides a set of skills and agents to streamline the development process.
Key features include interactive brainstorming, detailed planning, code review, and knowledge compounding, all of which work together to reduce complexity and improve overall quality. The plugin is available for various platforms, including Claude Code, Codex, Copilot, and more, with installation instructions provided for each.
Technical highlights of the plugin include its
37 skills and 51 agents, which can be used to automate tasks, provide guidance, and facilitate collaboration. The plugin also includes a range of tools for debugging, testing, and validation, making it a comprehensive solution for development teams.
The target audience for the Compound Engineering plugin includes developers, engineers, and development teams looking to improve their workflow, reduce technical debt, and increase productivity. By leveraging the plugin's features and agents, teams can work more efficiently, effectively, and with greater ease.
In summary, the Compound Engineering plugin is a powerful tool for streamlining development and improving overall quality - with its robust set of skills and agents, it's a game-changer for teams looking to work smarter, not harder.
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🧠 Channel: https://t.me/GithubRe15 221
💻 Scrap
🛠 Scraperr is a self-hosted application designed to accurately extract data from websites using XPath selectors.
🔰 It provides a convenient interface for managing scraping tasks, viewing and exporting data.
🔰 Key features include XPath-based extraction, queue management, scraping all pages of a single domain, adding custom headers, automatic media downloading, and visualizing results in tables.
🔰 The application is intended only for sites where scraping is allowed, and the developer is not responsible for possible abuse.
🔗Links:
https://github.com/jaypyles/Scraperr
#Scraperr #WebScraping #XPath #SelfHosted #DataExtraction #DevTools
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15 221
🔍 Deep-diving into microsoft/markitdown — fresh off the trending list.
🔗 https://github.com/microsoft/markitdown
📝 Python tool for converting files and office documents to Markdown.
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MarkItDown is a lightweight Python utility that converts various file formats to Markdown, ideal for use with Large Language Models (LLMs) and text analysis pipelines. It supports a wide range of file types, including PDF, PowerPoint, Word, Excel, images, audio, HTML, and more. The goal is to preserve important document structure and content as Markdown, making it easily consumable by text analysis tools.
Key features include:
-
convert_stream() and convert_local() functions for flexible conversion
- Support for optional dependencies for specific file formats, such as [pdf], [docx], and [pptx]
- Plugin architecture for extending functionality, including the markitdown-ocr plugin for Optical Character Recognition (OCR)
- Integration with Azure Content Understanding for higher-quality conversion and structured field extraction
- Python API for easy integration into existing workflows
To get started, simply install MarkItDown using pip install 'markitdown[all]' and use the command-line interface or Python API to convert your files. With MarkItDown, you can easily convert your files to Markdown and unlock the power of LLMs and text analysis pipelines. Convert your files to Markdown in minutes, and start analyzing your data with ease - MarkItDown makes it easy.
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🧠 Channel: https://t.me/GithubRe15 221
🔥 harry0703/MoneyPrinterTurbo is trending — and it deserves your attention.
🔗 https://github.com/harry0703/MoneyPrinterTurbo
📝 利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.
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MoneyPrinterTurbo is an open-source project that allows users to generate high-definition videos with customizable themes, music, and subtitles. The project uses a Model-View-Controller (MVC) architecture and supports both
API and Web interface interactions.
To use MoneyPrinterTurbo, users can provide a video theme or keyword, and the system will automatically generate a video script, video materials, subtitles, and background music. The project supports various video sizes, including 9:16 and 16:9, and allows for batch video generation.
The project has several technical highlights, including support for AI-generated video scripts, multi-language subtitles, and background music. It also supports various LLM providers, such as OpenAI and Azure.
MoneyPrinterTurbo is suitable for users who want to generate high-quality videos quickly and easily. The project is open-source and has a permissive license, making it accessible to a wide range of users.
To get started with MoneyPrinterTurbo, users can follow the quick start guide in the project's README file. The guide provides step-by-step instructions for installing the project, configuring the environment, and generating videos.
In summary, MoneyPrinterTurbo is a powerful tool for generating high-quality videos with customizable themes, music, and subtitles. With its open-source nature and permissive license, it is an excellent choice for users who want to create engaging videos quickly and easily.
Automate your video creation with MoneyPrinterTurbo - no video editing experience required!
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🧠 Channel: https://t.me/GithubRe
15 221
⚡ codecrafters-io/build-your-own-x is making waves. Here's the full picture.
🔗 https://github.com/codecrafters-io/build-your-own-x
📝 Master programming by recreating your favorite technologies from scratch.
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The codecrafters-io/build-your-own-x GitHub repository is a collection of step-by-step guides for building various technologies from scratch. It covers a wide range of topics, including 3D renderers, AI models, blockchains, bots, databases, and more. The repository provides tutorials and examples in different programming languages, such as
C++, Java, Python, and JavaScript. Whether you're a beginner or an experienced developer, this repository offers a valuable resource for learning and exploring new technologies. The guides are designed to be practical and hands-on, allowing you to build and experiment with your own projects. So, what I cannot create, I do not understand - start building and learning with codecrafters-io/build-your-own-x today! Build something from scratch, and you'll never see it the same way again.
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🧠 Channel: https://t.me/GithubRe15 221
🌟 DataTalksClub/data-engineering-zoomcamp caught my eye on GitHub Trending today.
🔗 https://github.com/DataTalksClub/data-engineering-zoomcamp
📝 Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼
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The Data Engineering Zoomcamp is a free 9-week course that covers the fundamentals of data engineering. It's designed to help you build an end-to-end data pipeline from scratch, with hands-on experience using industry-standard tools and best practices.
Key features of the course include structured modules, hands-on workshops, and a final project to reinforce your learning. You'll learn about
containerization, infrastructure as code, workflow orchestration, data warehousing, and analytics engineering.
The course is suitable for anyone with basic coding experience and familiarity with SQL. No prior data engineering experience is necessary. You can enroll in the course by registering for the next cohort or following the self-paced learning path.
The course has a strong community and support system, with a dedicated #course-data-engineering channel on Slack for discussions and troubleshooting.
The course is taught by experienced instructors, including Alexey Grigorev and Michael Shoemaker, and is sponsored by companies like Kestra and Bruin.
Overall, the Data Engineering Zoomcamp is a great resource for anyone looking to learn data engineering fundamentals and build a career in the field.
So, what are you waiting for? Join the course and start building your skills today - it's a free 9-week course that can change your career!
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🧠 Channel: https://t.me/GithubRe
15 221
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15 221
🌟 hardikpandya/stop-slop caught my eye on GitHub Trending today.
🔗 https://github.com/hardikpandya/stop-slop
📝 A skill file for removing AI tells from prose
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The Stop Slop GitHub repository is a skill designed to remove AI tells from prose, making your writing sound more human. The key features include a set of rules and references that help catch and remove predictable phrases, structures, and rhythms.
To use it, simply add the folder as a skill or upload the
SKILL.md and reference files to your project knowledge. You can also include SKILL.md in your system prompt for API calls.
The repository catches various patterns such as banned phrases, structural clichés, and sentence-level rules, and even provides a scoring system to rate your writing.
This repository is perfect for writers and developers looking to improve their writing skills and make their content sound more authentic.
In a nutshell, Stop Slop helps you write like a human, not a robot - so stop the slop and start writing.
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🧠 Channel: https://t.me/GithubRe
15 221
💡 affaan-m/ECC just hit the trending charts — here's why it matters.
🔗 https://github.com/affaan-m/ECC
📝 The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
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ECC is an open-source, harness-native operator system for agentic work, built from real-world multi-harness engineering workflows. It's designed to work across various AI agent harnesses, including Codex, Claude Code, Cursor, OpenCode, and more.
The system provides a complete set of features, including skills, instincts, memory optimization, continuous learning, security scanning, and research-first development.
To get started with ECC, you can follow the
HERMES setup guide and review the release notes and cross-harness architecture documentation.
Key features include:
- Token optimization
- Memory persistence
- Continuous learning
- Verification loops
- Parallelization
- Subagent orchestration
ECC is suitable for developers, engineers, and researchers working with AI agent harnesses.
Technical highlights include support for multiple programming languages, such as Python, Java, Go, and TypeScript.
In summary, ECC is a powerful tool for building and managing AI agent workflows, and its open-source nature makes it a great choice for anyone looking to automate and optimize their workflows - ECC is the future of agentic work, and the future is now.
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🧠 Channel: https://t.me/GithubRe
15 221
🌟 DigitalPlatDev/FreeDomain caught my eye on GitHub Trending today.
🔗 https://github.com/DigitalPlatDev/FreeDomain
📝 DigitalPlat FreeDomain: Free Domain For Everyone
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DigitalPlat FreeDomain is a platform that offers free domain names to individuals and organizations, promoting a more accessible web. The goal is to make the internet an open space where everyone can have their own online presence, regardless of budget.
Key features include free domain registration with various extensions like
.DPDNS.ORG and .US.KG, and the freedom to host with your preferred DNS provider. To get started, simply visit the DigitalPlat FreeDomain Dashboard and follow the tutorial.
From a technical standpoint, the project has grown significantly, now supporting over 500,000 domains. The founder, Edward Hsing, shares the story of how this started as a small DNS experiment and evolved into a reliable service.
The target audience is anyone looking to establish an online presence without the burden of domain costs. Whether you're a developer, blogger, or just starting out, DigitalPlat FreeDomain is a great option.
In short, DigitalPlat FreeDomain is a game-changer for those who want to create a website without breaking the bank - Claim your free domain and start building your online presence today!
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🧠 Channel: https://t.me/GithubRe15 221
💡 Crosstalk-Solutions/project-nomad just hit the trending charts — here's why it matters.
🔗 https://github.com/Crosstalk-Solutions/project-nomad
📝 Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere.
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Project N.O.M.A.D. is a self-contained, offline-first knowledge and education server that empowers users with critical tools and AI, anytime, anywhere. Key features include an AI chat with knowledge base, information library, education platform, offline maps, data tools, and notes.
To get started, users can follow the
Quick Install guide for Debian-based operating systems. For more control, advanced users can use the Docker Compose template to customize their installation.
Technical highlights of Project N.O.M.A.D. include its management UI and API, which orchestrate a collection of containerized tools and resources via Docker. The project is suitable for users who want to access knowledge and education resources offline, including students, researchers, and individuals in areas with limited internet connectivity.
The project is licensed under the Apache License 2.0 and has a growing community with resources like a website, Discord channel, and benchmark leaderboard.
In a nutshell, Project N.O.M.A.D. is the ultimate offline companion for knowledge seekers - empowering minds, anywhere.
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🧠 Channel: https://t.me/GithubRe15 221
🎯 Biohub/esm landed on trending. Worth a proper look.
🔗 https://github.com/Biohub/esm
📝 No description.
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The Biohub/esm GitHub repository presents a groundbreaking world model of protein biology, leveraging the latest advancements in Evolutionary Scale Modeling (ESM). This comprehensive system comprises three primary components:
ESMC, ESMFold2, and ESM Atlas.
ESMC is a state-of-the-art protein language model trained on billions of protein sequences, allowing it to learn and represent the rules of protein biology. ESMFold2 builds upon ESMC and is a state-of-the-art structure prediction model that can predict high-resolution, all-atom 3D protein structures directly from amino acid sequences. The ESM Atlas is a vast map of 6.8 billion proteins, organized according to the internal world model of ESMC, enabling the prediction of over one billion structures.
These tools can be utilized through the Biohub Platform or by running the models locally with Hugging Face. The repository provides extensive documentation, including tutorials and preprints, to facilitate understanding and usage. The target audience includes researchers, scientists, and developers interested in protein biology, structure prediction, and world modeling.
Here is a simple example of running ESMC locally:
import torch
from transformers import AutoModelForMaskedLM, AutoTokenizer
# example GFP sequence
sequences = ["MSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPTLVTTFSYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTLVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITHGMDELYK"]
model = AutoModelForMaskedLM.from_pretrained(
"Biohub/ESMC-6B",
device_map="auto",
).eval()
tokenizer = AutoTokenizer.from_pretrained("Biohub/ESMC-6B")
inputs = tokenizer(sequences, return_tensors="pt", padding=True)
inputs = {k: v.to(model.device) for k, v in inputs.items()}
with torch.inference_mode():
output = model(**inputs)
esm library and import the necessary modules. With Biohub/esm, unlock the power of world modeling in protein biology and discover new frontiers in protein structure prediction and design. The future of protein biology is here, and it's being modeled with unprecedented accuracy.
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🧠 Channel: https://t.me/GithubRe