Github Top Repositories
Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Mostrar más📈 Análisis del canal de Telegram Github Top Repositories
El canal Github Top Repositories (@githubre) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 15 231 suscriptores, ocupando la posición 13 394 en la categoría Educación y el puesto 26 058 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 15 231 suscriptores.
Según los últimos datos del 07 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 379, y en las últimas 24 horas de 11, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 0.92%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.62% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 140 visualizaciones. En el primer día suele acumular 95 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 1.
- Intereses temáticos: El contenido se centra en temas clave como repository, fork, programming, statistic, description.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 08 noviembre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.
技术架构 包括 Claude Code Skill、NotebookLM API、MCP 工具、markitdown 文件转换等。
使用示例 包括付费文章转播客、播客转 PPT、电子书转深度分析等。
总的来说,Anything → NotebookLM 是一个非常有用的工具,可以帮助你快速将任何内容转换为多种格式,非常适合研究、学习、工作等场景。
结论:使用 Anything → NotebookLM,可以快速将任何内容转换为多种格式,节省时间,提高效率。 赶快试试吧!
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🧠 Channel: https://t.me/GithubReskills.sh installer and follow the prompts to set up the skills you want. The skills are designed to be small, easy to adapt, and composable, working with any model.
Technical highlights include the use of npx skills@latest add mattpocock/skills for installation and the /setup-matt-pocock-skills command to configure your skills.
These skills are suitable for developers and engineers looking to improve their workflow with coding agents.
In short, mattpocock/skills helps you work better with coding agents - try it and supercharge your development workflow!
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🧠 Channel: https://t.me/GithubRebun command-line tool implements a test runner, script runner, and Node.js-compatible package manager, making it a great option for developers who want to simplify their workflow.
With bun, you can run scripts, test your code, and install packages with ease. It also supports TSX and JSX out-of-the-box. The toolkit is highly customizable, with a wide range of plugins and configurations available.
Technical highlights of Bun include its fast JavaScript runtime, written in Zig and powered by JavaScriptCore, as well as its Node.js compatibility. The toolkit is suitable for developers of all levels, from beginners to experienced professionals.
To get started with Bun, you can install it using a simple curl command, and then upgrade to the latest version using the bun upgrade command.
In short, Bun is a game-changer for JavaScript and TypeScript development - it's fast, efficient, and easy to use.
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🧠 Channel: https://t.me/GithubRereal-time video intelligence, downstream analytics, and agentic and offline processing. The blueprint is designed for video analysts and IT engineers, as well as GenAI developers and machine learning engineers, providing a range of configuration options and customization possibilities.
To get started, users can follow the Quickstart Guide for a launchable deployment or Docker Compose deployment, with system requirements including Ubuntu 22.04 or 24.04, NVIDIA Driver 580.105.08, and Docker 27.2.0+.
print("NVIDIA VSS blueprint streamlines video analytics and summarization with AI")
One-liner takeaway: The NVIDIA VSS blueprint revolutionizes video analytics by integrating AI-powered vision agents for smarter, more efficient processing and summarization.
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🧠 Channel: https://t.me/GithubRestructured access to 1,650 n8n nodes, including core and community nodes, with detailed schemas and documentation. It also provides real-world examples and a template library to help users build efficient workflows.
To get started, users can try the free tier on dashboard.n8n-mcp.com with 100 tool calls per day, or self-host the server using npx, Docker, or Railway. The project supports multiple AI-powered IDEs and tools, including Claude Code, Visual Studio Code, and Cursor.
Key features include node discovery, configuration, and validation, as well as workflow building and deployment. The project also provides a comprehensive guide for setting up and using n8n-MCP with Claude Projects.
The target audience includes developers, marketers, and analysts who want to automate their workflows efficiently using n8n and AI tools.
Technical highlights include support for multiple programming languages, a large template library, and a robust validation system.
In summary, n8n-MCP is a powerful tool that enables AI assistants to work seamlessly with n8n nodes, making it an essential resource for anyone looking to automate their workflows with ease: Automate your workflows with n8n-MCP and take your productivity to the next level!
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🧠 Channel: https://t.me/GithubReSKILL.md file containing instructions and metadata. You can also use the template skill provided as a starting point to create your own custom skills.
The repository is divided into several sections, including skills, spec, and template. The skills section contains a wide range of example skills, while the spec section outlines the Agent Skills specification. The template section provides a template for creating new skills.
To try out the skills in the repository, you can register the repository as a Claude Code Plugin marketplace and install specific skills. You can also use the skills in Claude.ai or upload custom skills via the Claude API.
One of the key technical highlights of the repository is the use of YAML frontmatter in the SKILL.md files to define the skill's metadata. This allows for easy creation and modification of skills.
The repository is aimed at a wide range of audiences, including developers, designers, and enterprise users. Whether you're looking to create custom skills or simply want to learn more about the capabilities of Claude, this repository is a great resource.
In short, the anthropics/skills repository is a powerful tool for unlocking the full potential of Claude - and with great skills comes great AI power!
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🧠 Channel: https://t.me/GithubReTOML configuration, users can easily set up and customize Telegraf. It compiles into a standalone static binary, making deployment a breeze.
Telegraf is designed for a wide range of users, from developers to system administrators, who need to collect and process data from various sources. Whether you're working with devices, logs, messaging, or system monitoring, Telegraf has got you covered.
To get started, users can define a TOML configuration with their desired plugins and settings, and then pass it to Telegraf. The agent will collect data from inputs at each interval and send it to outputs at each flush interval.
With a large community of over 1,200 contributors, Telegraf is constantly evolving and improving. The project has a comprehensive documentation, including tutorials, reference materials, and a contributing guide for those who want to get involved.
In a nutshell, Telegraf is the go-to solution for data collection and processing - and with its flexibility and customizability, it's an essential tool for anyone working with data. So, what are you waiting for? Join the Telegraf community today and start collecting, processing, and writing your data with ease!
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🧠 Channel: https://t.me/GithubReRuView runs on edge hardware, with no cloud or internet required, and uses spiking neural networks that adapt in under 30 seconds. The system is ideal for low-power edge applications, such as elderly care, hospital patient monitoring, and retail occupancy tracking. With RuView, you can turn ordinary WiFi into a spatial intelligence system — and that's a game-changer.
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🧠 Channel: https://t.me/GithubRepip install supertonic and generate speech with the provided examples. The repository includes ready-to-use examples across multiple ecosystems, such as Python, Node.js, browser, mobile, and native runtimes.
From a technical perspective, Supertonic utilizes ONNX Runtime for cross-platform inference and supports batch processing for improved throughput. The system is designed to handle natural text inputs with complex prose, punctuation, abbreviations, and proper nouns.
With support for 31 languages and various expression tags like <laugh>, <breath>, and <sigh>, Supertonic is an ideal choice for developers seeking a flexible and efficient text-to-speech solution.
In a nutshell, Supertonic is the perfect tool for anyone looking to add high-quality, on-device text-to-speech capabilities to their application - it's fast, private, and accurate, making it a game-changer in the world of TTS technology.
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🧠 Channel: https://t.me/GithubReAgent Skills standard. This repository, created by K-Dense, provides a wide range of skills across multiple scientific domains, including bioinformatics, cheminformatics, proteomics, and more.
These skills enable your AI agent to seamlessly work with specialized scientific libraries, databases, and tools. The repository includes 100+ scientific databases, 70+ optimized Python package skills, and 9 scientific integration skills, among others.
To get started, you can install the skills using npx or the GitHub CLI. The skills are well-documented, with examples, use cases, and best practices.
This repository is maintained and supported by the K-Dense team, with regular updates and community contributions.
In summary, the Scientific Agent Skills repository is a powerful tool for transforming your AI agent into a research assistant capable of executing complex multi-step scientific workflows.
With the ability to access 100+ databases and utilize 70+ optimized Python packages, this repository is a game-changer for scientists and researchers: Transform your AI coding agent into an 'AI Scientist' and accelerate your research today!
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🧠 Channel: https://t.me/GithubRebasic workflow outlined in the documentation.
From a technical standpoint, Superpowers uses a subagent-driven-development process, where agents work through each engineering task, inspecting and reviewing their work. This process emphasizes test-driven development, systematic debugging, and complexity reduction.
Superpowers is designed for anyone looking to improve their coding agent's productivity, including developers, engineers, and researchers.
In short, Superpowers helps your coding agents work smarter, not harder - automate your coding workflow and focus on the big picture.
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🧠 Channel: https://t.me/GithubReMemory Tree and Obsidian Wiki features allow you to create a local-first knowledge base built from your data and activity, with everything canonicalized into Markdown chunks stored in SQLite on your machine. Smart token compression (TokenJuice) reduces cost and latency by up to 80%.
To get started, you can download OpenHuman from the website or run the installation script. The project is still in early beta, but it's already showing great promise.
The target audience for OpenHuman includes developers, researchers, and individuals looking for a powerful and private AI assistant. With its native voice and messaging channels features, OpenHuman is an excellent choice for those who want a seamless and integrated experience.
Technical highlights of OpenHuman include its use of Rust, Node.js, and SQLite, as well as its support for Git and CMake. The project is actively maintained and has a growing community of contributors.
In short, OpenHuman is a game-changer for those who want a personal AI assistant that's both powerful and private. With its innovative features and technical highlights, it's an exciting project to watch and contribute to. Here's a simple way to get started:
curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bash
One-liner takeaway: OpenHuman is the ultimate AI sidekick that learns about you in minutes, not weeks, and helps you get more done with less hassle!
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🧠 Channel: https://t.me/GithubRe