Github Top Repositories
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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 15 212 suscriptores, ocupando la posición 13 433 en la categoría Educación y el puesto 26 115 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 15 212 suscriptores.
Según los últimos datos del 04 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 407, y en las últimas 24 horas de 27, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 0.93%. 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 142 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 05 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.
15 212
Suscriptores
+2724 horas
+807 días
+40730 días
Archivo de publicaciones
15 215
💡 TencentCloud/CubeSandbox just hit the trending charts — here's why it matters.
🔗 https://github.com/TencentCloud/CubeSandbox
📝 Instant, Concurrent, Secure & Lightweight Sandbox for AI Agents.
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Welcome to CubeSandbox, an instant, concurrent, secure, and lightweight sandbox service designed for AI Agents. This high-performance sandbox is built on RustVMM and KVM, offering both single-node deployment and easy scaling to multi-node clusters. It's also compatible with the E2B SDK, allowing for seamless migration and creating a hardware-isolated sandbox in under 60ms with less than 5MB of memory overhead.
Key features include sub-60ms boot, high density, auto pause/resume, hardware-level isolation, and E2B compatibility. The service also provides a web console for managing sandboxes, templates, and nodes, as well as a credential vault for secure key management and egress control for domain allowlists and audit logs.
To get started, follow the quick start guide, which walks you through provisioning a server, installing Cube Sandbox, creating a sandbox template, and running your first sandbox. You can also explore the documentation and changelog for more information.
CubeSandbox is ideal for developers and organizations looking for a secure, high-performance, and scalable sandbox solution for their AI Agents. With its
extreme isolation level, sub-millisecond boot speed, and ultra-low memory overhead, CubeSandbox is the perfect choice for those who want to run thousands of agents on a single node.
In short, CubeSandbox is the ultimate sandbox solution for AI Agents - fast, secure, and scalable.
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🧠 Channel: https://t.me/GithubRe15 215
⚡ bradautomates/claude-video is making waves. Here's the full picture.
🔗 https://github.com/bradautomates/claude-video
📝 Give Claude the ability to watch any video. /watch downloads, extracts frames, transcribes, hands it all to Claude.
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The bradautomates/claude-video GitHub repository enables Claude to watch and understand videos by extracting frames, captions, and audio transcripts. Key features include support for various video sources, automatic caption detection, and frame extraction using
yt-dlp and ffmpeg. Users can install the skill via Claude Code, Codex, Cursor, or other hosts using npx skills add bradautomates/claude-video -g.
The skill is useful for analyzing content, diagnosing bugs, summarizing videos, and more.
One-liner takeaway: With Claude Video, you can unlock the full potential of video analysis and understanding, making it an indispensable tool for anyone looking to watch and learn from videos.
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🧠 Channel: https://t.me/GithubRe15 215
💡 wonderwhy-er/DesktopCommanderMCP just hit the trending charts — here's why it matters.
🔗 https://github.com/wonderwhy-er/DesktopCommanderMCP
📝 This is MCP server for Claude that gives it terminal control, file system search and diff file editing capabilities
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Desktop Commander MCP is a powerful tool that lets you search, update, manage files, and run terminal commands with AI. It offers
remote AI control, file preview UI, and enhanced terminal commands with interactive process control. You can execute code in memory without saving files and perform instant data analysis on CSV, JSON, and Excel files.
The tool supports native Excel file operations, PDF support, and DOCX support, allowing you to read, write, edit, and search these files. You can also interact with running processes like SSH, databases, and development servers.
To get started, you can install Desktop Commander MCP through various methods, including npx, bash script installer, Smithery, or docker installation. Each method has its own advantages, such as auto-updates and sandboxed environments.
Desktop Commander MCP is designed for developers who want to streamline their workflow and automate tasks using AI. With its comprehensive audit logging and security hardening features, you can ensure the security and integrity of your data.
In short, Desktop Commander MCP is a game-changer for anyone looking to revolutionize their workflow with AI-powered tools. Try it out and experience the power of AI-driven development!
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🧠 Channel: https://t.me/GithubRe
15 215
🌟 Diolinux/PhotoGIMP caught my eye on GitHub Trending today.
🔗 https://github.com/Diolinux/PhotoGIMP
📝 A Patch for GIMP 3+ for Photoshop Users
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Transform GIMP into a Photoshop-like experience with PhotoGIMP, a free, community-driven patch. Designed for users switching from Adobe Photoshop, it reorganizes GIMP's tool layout, keyboard shortcuts, and UI to feel familiar.
Key features include a Photoshop-like tool layout, custom splash screen, maximized canvas space, and Photoshop keyboard shortcuts.
To get started, ensure you have GIMP 3.0 or newer installed, then download and extract the PhotoGIMP patch, overwriting GIMP's configuration files. Technical highlights include the replacement of GIMP's configuration files, such as shortcutsrc, toolrc, and sessionrc, to match Photoshop's layout and functionality.
Audience: Photographers, graphic designers, and digital artists seeking a free, open-source alternative to Adobe Photoshop. Whether you're a seasoned pro or a beginner, PhotoGIMP helps you transition to GIMP seamlessly.
In a nutshell, PhotoGIMP is all about unlocking GIMP's full potential with a UI that's intuitive for Photoshop users - making the switch to free and open-source editing a breeze.
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🧠 Channel: https://t.me/GithubRe
15 215
💡 alibaba/zvec just hit the trending charts — here's why it matters.
🔗 https://github.com/alibaba/zvec
📝 A lightweight, lightning-fast, in-process vector database
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Meet Zvec, an open-source, in-process vector database that's lightweight, lightning-fast, and designed to embed directly into applications. It delivers production-grade, low-latency, and scalable similarity search with minimal setup. Key features include blazing fast searches, simple installation, and support for dense and sparse vectors, full-text search, and hybrid search.
Technical highlights of Zvec include its ability to search billions of vectors in milliseconds, durable storage with write-ahead logging, and concurrent access. It also offers official SDKs for multiple languages, including
Python, Node.js, Go, and Rust.
To get started with Zvec, you can install it via pip with pip install zvec or use one of the other language-specific installation methods. The quickstart guide provides a one-minute example of how to create a collection, insert documents, and search by vector similarity.
Zvec is ideal for developers and data scientists who need a fast and efficient vector database for their applications. Its performance at scale makes it suitable for demanding production workloads.
In summary, Zvec is a powerful and easy-to-use vector database that's perfect for building scalable and efficient similarity search applications. Join the community and start contributing to Zvec today - with Zvec, your search just got a whole lot faster!
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🧠 Channel: https://t.me/GithubRe15 215
🌟 obra/superpowers caught my eye on GitHub Trending today.
🔗 https://github.com/obra/superpowers
📝 An agentic skills framework & software development methodology that works.
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Superpowers is a software development methodology for coding agents, built on top of composable skills and initial instructions. It helps your agent understand what you're trying to do, creates an implementation plan, and launches a subagent-driven development process.
Key features include test-driven development, systematic debugging, and collaboration tools like brainstorming, writing plans, and requesting code reviews.
To
use Superpowers, install it as a plugin in your coding agent, such as Claude Code, Antigravity, or Codex App. The installation process varies depending on the agent.
From a technical standpoint, Superpowers uses a skills library with testing, debugging, and collaboration tools. It emphasizes simplicity, systematic processes, and evidence-based development.
Target audience includes developers, coding agents, and anyone looking to streamline their development workflow.
In short, Superpowers transforms your coding agent into a collaborative development partner - try it out and unlock your agent's full potential!
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🧠 Channel: https://t.me/GithubRe15 215
📌 Spotted on GitHub Trending: asgeirtj/system_prompts_leaks — let's break it down.
🔗 https://github.com/asgeirtj/system_prompts_leaks
📝 Extracted system prompts from Anthropic - Claude Fable 5, Opus 4.8, Claude Code, Claude Design. OpenAI - ChatGPT 5.5 Thinking, GPT 5.5 Instant, Codex. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly.
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The asgeirtj/system_prompts_leaks GitHub repository is a treasure trove of system prompt instructions for various AI chatbots, including Claude, ChatGPT, and Gemini. This repo is all about transparency, offering a behind-the-scenes look at the hidden rules governing these AI models. With
system prompts for different models and versions, you can explore how these AI chatbots are designed to operate. The repo is regularly updated with new additions, such as Claude Sonnet 5 and Gemini 3.5 Flash. Whether you're a developer, researcher, or simply an AI enthusiast, this repository is a valuable resource for understanding the inner workings of AI chatbots. Stay ahead of the curve with the latest system prompts and diff updates, and discover the power of transparency in AI development. One key takeaway: Knowing the system prompts can help you unlock the full potential of AI chatbots.
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🧠 Channel: https://t.me/GithubRe
15 215
🌟 iOfficeAI/OfficeCLI caught my eye on GitHub Trending today.
🔗 https://github.com/iOfficeAI/OfficeCLI
📝 OfficeCLI is the first and best Office suite purpose-built for AI agents to read, edit, and automate Word, Excel, and PowerPoint files. Free, open-source, single binary, no Office installation required.
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The OfficeCLI is a revolutionary tool that empowers AI agents to control Word, Excel, and PowerPoint with ease. This open-source project provides a
single binary that works everywhere, with no Office installation or dependencies required. The built-in HTML rendering engine allows AI agents to "see" and reproduce documents with high fidelity.
To get started, AI agents can use a one-liner command to install the necessary skills, while humans can use the officecli command to create, read, and edit Office documents. Developers can also experiment with the tool using a 30-second live demo.
The OfficeCLI supports a wide range of features, including creating documents from scratch, reading and modifying text and structure, and analyzing formatting issues. It also provides extensive support for Word, Excel, and PowerPoint, including features like tables, shapes, and charts.
Whether you're an AI agent, human, or developer, the OfficeCLI is an indispensable tool for working with Office documents.
Takeaway: With OfficeCLI, AI agents can create stunning Office documents in a snap - curl -fsSL https://officecli.ai/SKILL.md and watch the magic unfold!
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🧠 Channel: https://t.me/GithubRe
15 215
🎯 argoproj/argo-cd landed on trending. Worth a proper look.
🔗 https://github.com/argoproj/argo-cd
📝 Declarative Continuous Deployment for Kubernetes
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Meet Argo CD, a declarative GitOps continuous delivery tool for Kubernetes. Its purpose is to automate application deployment and lifecycle management, making it auditable and easy to understand. Key features include declarative application definitions, automated deployment, and easy environment management.
To get started with
Argo CD, you can use the live demo at https://cd.apps.argoproj.io/ or check out the complete documentation at https://argo-cd.readthedocs.io/.
From a technical standpoint, Argo CD uses GitOps principles to manage production environments in Kubernetes. It's suitable for various audiences, including developers, DevOps teams, and enterprises looking to simplify and automate deployments using GitOps.
One of the major benefits of using Argo CD is that it allows you to manage your application configurations and environments in a declarative and version-controlled way. This approach makes it easier to track changes and ensure consistency across different environments.
In terms of technical highlights, Argo CD supports automated deployment, rollbacks, and self-healing, making it a robust tool for managing complex applications.
The Argo CD community is active and offers various resources, including blogs, presentations, and tutorials, to help you get started with the tool.
In a nutshell, Argo CD is all about simplifying and automating deployments using GitOps - and that's a game-changer for DevOps teams!
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🧠 Channel: https://t.me/GithubRe
15 215
🌟 mvanhorn/last30days-skill caught my eye on GitHub Trending today.
🔗 https://github.com/mvanhorn/last30days-skill
📝 AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
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Introducing /last30days, an AI agent-led search engine that scores results based on real people's engagement, not editors. It searches multiple platforms like Reddit, X, YouTube, and GitHub in parallel, providing a more accurate picture of what's happening now.
Key features include zero config, intelligent search, and cross-source cluster merging. The engine is constantly updated with new sources and features, making it a powerful tool for anyone looking to stay informed.
Technical highlights include the use of a Python pre-research brain to resolve topics and entities, and a second judge to score results for humor and virality. The engine also supports shareable HTML briefs, making it easy to share research with others.
Usage is simple: just type "/last30days" followed by your topic, and the engine will provide a brief summary of what's happening now. You can also use the engine to compare tools, understand the world, or learn something fast.
Audience includes anyone looking to stay informed about the latest developments in their field, from developers and researchers to business professionals and curious individuals.
The engine is available on various platforms, including Claude Code, Codex, and GitHub, and can be installed using
npx skills add mvanhorn/last30days-skill -g.
In short, /last30days is a game-changer for anyone looking to stay informed: it's like having a superpower that lets you know what's actually happening now, not just what editors think you should know.
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🧠 Channel: https://t.me/GithubRe
15 215
🎯 prisma/prisma landed on trending. Worth a proper look.
🔗 https://github.com/prisma/prisma
📝 Next-generation ORM for Node.js & TypeScript | PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, MongoDB and CockroachDB
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Hey there, junior dev! Let's dive into the Prisma GitHub repo. Prisma is a next-generation ORM that helps you work with databases in a more efficient and type-safe way. It consists of three main tools: Prisma Client, Prisma Migrate, and Prisma Studio.
You can use Prisma Client in any Node.js or TypeScript backend application, and it supports various databases like PostgreSQL, MySQL, and SQLite. To get started, you'll need to define your application models in a
prisma.schema file, which allows you to configure generators and data sources.
Here's an example of what the schema file might look like:
datasource db {
provider = "postgresql"
}
generator client {
provider = "prisma-client"
output = "../generated"
}
model Post {
id Int @id @default(autoincrement())
title String
content String?
published Boolean @default(false)
author User? @relation(fields: [authorId], references: [id])
authorId Int?
}
model User {
id Int @id @default(autoincrement())
email String @unique
name String?
posts Post[]
}
You can then use the Prisma Client to send queries to your database. For example, you can retrieve all User records like this:
const allUsers = await prisma.user.findMany()15 215
💡 TencentCloud/TencentDB-Agent-Memory just hit the trending charts — here's why it matters.
🔗 https://github.com/TencentCloud/TencentDB-Agent-Memory
📝 TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.
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The TencentDB Agent Memory repository provides a memory solution for AI agents, enabling them to learn workflows, retain task context, and reuse past experience. The system consists of two main components: symbolic memory for in-task information overload and memory layering for cross-session experience.
Key features include:
-
Memory layering: a hierarchical storage approach that distills fragmented conversations into structured personas and scenes.
- Symbolic memory: a Mermaid symbol graph that encodes task state transitions, reducing token usage and improving task success.
Technical highlights:
- Integrates with OpenClaw, reducing token usage by up to 61.38% and improving pass rate by 51.52%.
- Supports Hermes Agent, enabling memory-enabled capabilities.
This solution is designed for developers and engineers looking to enhance their AI agents with efficient memory capabilities.
The punchy one-liner takeaway: Empower your AI agents to remember what matters, so humans can focus on what truly counts.
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🧠 Channel: https://t.me/GithubRe
15 215
🌟 ruvnet/RuView caught my eye on GitHub Trending today.
🔗 https://github.com/ruvnet/RuView
📝 π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.
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RuView is a revolutionary WiFi sensing platform that transforms ordinary WiFi into a spatial intelligence system. It detects people, measures breathing and heart rate, tracks movement, and monitors rooms — all through walls, in the dark, with no cameras or wearables. Just physics.
Key Features:
- Presence and occupancy detection
- Vital signs measurement (breathing rate and heart rate)
- Activity recognition (walking, sitting, gestures, falls)
- Environment mapping (RF fingerprinting)
- Sleep quality monitoring
Technical Highlights:
- Runs on low-cost ESP32 sensors with Cognitum Seed for persistent memory and AI integration
- Uses Channel State Information (CSI) and spiking neural networks for real-time learning
- Compatible with major smart-home ecosystems (Home Assistant, Apple Home, Google Home, Amazon Alexa)
-
pip install ruview for Python integration
Audience:
- Developers interested in spatial intelligence and WiFi sensing
- Smart home enthusiasts
- Researchers in fields like computer vision, machine learning, and IoT
Usage:
- Drop into any Home Assistant install with one --mqtt flag
- Pair with Apple Home, Google Home, or Alexa as a Matter Bridge
- Use with ESP32 hardware for live sensing or simulate with Docker
One-liner takeaway: RuView turns WiFi into a superpower, sensing your space without cameras, making it a game-changer for smart homes, healthcare, and beyond.
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🧠 Channel: https://t.me/GithubRe