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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 13 248 підписників, посідаючи 15 402 місце в категорії Освіта та 32 619 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 13 248 підписників.
За останніми даними від 08 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 357, а за останні 24 години на 10, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 1.16%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.75% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 153 переглядів. Протягом першої доби публікація в середньому набирає 99 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 09 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.
13 248
Підписники
+1024 години
+897 днів
+35730 день
Архів дописів
13 248
📌 Spotted on GitHub Trending: KeygraphHQ/shannon — let's break it down.
🔗 https://github.com/KeygraphHQ/shannon
📝 Shannon Lite is an autonomous, white-box AI pentester for web applications and APIs. It analyzes your source code, identifies attack vectors, and executes real exploits to prove vulnerabilities before they reach production.
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Shannon is an autonomous, white-box AI pentester for web applications and APIs. It analyzes source code, identifies attack vectors, and executes real exploits to prove vulnerabilities before they reach production. Key features include fully autonomous operation, reproducible proof-of-concept exploits, and code-aware dynamic testing.
Shannon is available in two editions: Shannon Lite (AGPL-3.0) for local testing and Shannon Pro (commercial) for organizations needing a single AppSec platform. Technical highlights include a Code Property Graph (CPG) combining the AST, control flow graph, and program dependence graph, and a two-stage pipeline with agentic static analysis and autonomous AI penetration testing. Audience includes developers, security professionals, and organizations looking for automated penetration testing. Here's a quick start example:
npx @keygraph/shannon setup
npx @keygraph/shannon start -u https://your-app.com -r /path/to/your-repo13 248
🎯 Light-Heart-Labs/DreamServer landed on trending. Worth a proper look.
🔗 https://github.com/Light-Heart-Labs/DreamServer
📝 Local AI anywhere, for everyone — LLM inference, chat UI, voice, agents, workflows, RAG, and image generation. No cloud, no subscriptions.
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Dream Server is an open-source, local-first AI stack that empowers individuals to self-host their AI infrastructure. The project's primary goal is to provide a sovereign AI solution, allowing users to run their AI models on their own hardware, without relying on cloud services or centralized providers.
Key features of Dream Server include:
- One-command installation: detects GPU, picks the right model, and launches all services
- Chatting in under 2 minutes: bootstrap mode enables instant chatting while the full model downloads in the background
- Full service stack: chat, agents, voice, workflows, search, RAG, image generation, and privacy tools, all pre-wired and talking to each other
From a technical standpoint, Dream Server supports various platforms, including
Linux, Windows, and macOS, with NVIDIA, AMD, and Intel Arc GPUs. The project also features hardware auto-detection, which selects the optimal model based on the user's hardware.
The target audience for Dream Server includes individuals and organizations seeking to maintain control over their AI infrastructure and data. With its user-friendly installation process and extensive documentation, Dream Server makes it possible for anyone to self-host their AI, regardless of their technical background.
Dream Server is the ultimate game-changer: Take back control of your AI, and never look back.
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🧠 Channel: https://t.me/GithubRe
13 248
📌 Spotted on GitHub Trending: K-Dense-AI/scientific-agent-skills — let's break it down.
🔗 https://github.com/K-Dense-AI/scientific-agent-skills
📝 A set of ready to use Agent Skills for research, science, engineering, analysis, finance and writing.
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The Scientific Agent Skills GitHub repository offers a comprehensive collection of 135 ready-to-use scientific and research skills for AI agents that support the open
Agent Skills standard. These skills enable AI agents to work with specialized scientific libraries, databases, and tools across multiple scientific domains, including bioinformatics, cheminformatics, proteomics, and more. The repository includes 100+ scientific databases, 70+ optimized Python package skills, and 9 scientific integration skills, as well as tools for analysis, communication, and research.
To get started, users can install the skills using npx or the GitHub CLI. The skills are designed to be easy to integrate and use, with comprehensive documentation and examples provided for each skill. The repository is regularly updated and maintained by the K-Dense team, with contributions from the community.
The target audience for this repository includes researchers, scientists, and developers who want to leverage AI to accelerate their research and workflows. With Scientific Agent Skills, users can transform their AI coding agent into an 'AI Scientist' capable of executing complex multi-step scientific workflows.
Takeaway: Unlock the full potential of your AI agent with Scientific Agent Skills and discover a new world of possibilities in scientific research and development.
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🧠 Channel: https://t.me/GithubRe13 248
🌟 dograh-hq/dograh caught my eye on GitHub Trending today.
🔗 https://github.com/dograh-hq/dograh
📝 Open Source Voice Agent Platform
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Dograh AI is an open-source, self-hostable platform for building production voice agents with a drag-and-drop workflow builder. It's a alternative to Vapi and Retell, allowing for full control and transparency.
Key features include a drag-and-drop workflow builder, telephony integration, and support for custom models.
docker-compose is used for easy setup and deployment.
Technical highlights include a modular architecture, real-time processing, and support for multiple languages. The platform is built on Python and uses Docker for containerization.
The platform is suitable for developers and businesses looking for a customizable and scalable voice AI solution.
To get started, simply run curl -o docker-compose.yaml https://raw.githubusercontent.com/dograh-hq/dograh/main/docker-compose.yaml && REGISTRY=ghcr.io/dograh-hq ENABLE_TELEMETRY=true docker compose up --pull alwayshttp://localhost:3010.
Dograh AI is licensed under the BSD 2-Clause License, ensuring freedom to use, modify, and distribute.
With Dograh AI, you can build a working voice bot in under 2 minutes - no coding required.
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🧠 Channel: https://t.me/GithubRe
13 248
💡 NirDiamant/agents-towards-production just hit the trending charts — here's why it matters.
🔗 https://github.com/NirDiamant/agents-towards-production
📝 End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
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The Agents Towards Production GitHub repository is your one-stop-shop for transforming AI agents into real-world products. This open-source playbook offers
28 production-grade tutorials covering stateful workflows, vector memory, web search APIs, and more. Key features include Docker deployment, security guardrails, GPU scaling, and multi-agent coordination. To get started, simply explore the tutorials and star the project to help others discover it. The repository is perfect for developers, data scientists, and AI enthusiasts looking to build production-ready GenAI agents. With its comprehensive guides and step-by-step tutorials, you'll be able to overcome common challenges and deploy your AI agents with confidence. Take your AI projects to the next level with Agents Towards Production - scale your AI agents from prototype to enterprise!
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🧠 Channel: https://t.me/GithubRe13 248
💡 tech-leads-club/agent-skills just hit the trending charts — here's why it matters.
🔗 https://github.com/tech-leads-club/agent-skills
📝 The secure, validated skill registry for professional AI coding agents. Extend Antigravity, Claude Code, Cursor, Copilot and more with absolute confidence.
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The Agent Skills repository provides a secure and validated skill registry for professional AI coding agents. It offers a hardened library of verified, tested, and safe capabilities, extending the functionality of agents like Claude Code, Cursor, and more.
Key features include:
-
on-demand skill fetching from a CDN
- caching for offline use
- interactive wizard for easy installation
- Support for multiple AI agents, including Claude Code and Cursor
Security & Trust are top priorities, with measures like:
- 100% open source (no binaries)
- static analysis in CI/CD
- immutable integrity via lockfiles and content hashing
To get started, use the npx @tech-leads-club/agent-skills command to launch an interactive wizard, or install globally with npm install -g @tech-leads-club/agent-skills.
The takeaway: with Agent Skills, you can extend your AI coding agents with confidence, knowing that each skill has been verified, tested, and secured to ensure a safe and reliable experience.
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🧠 Channel: https://t.me/GithubRe13 248
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13 248
🔥 BigBodyCobain/Shadowbroker is trending — and it deserves your attention.
🔗 https://github.com/BigBodyCobain/Shadowbroker
📝 Open-source intelligence for the global theater. Track everything from the corporate/private jets of the wealthy, and spy satellites, to seismic events in one unified interface. Hook an AI agent up to have it parse through data and find previously unseen correlations. The knowledge is available to all but rarely aggregated in the open, until now.
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Introducing ShadowBroker, a decentralized intelligence platform that aggregates real-time, multi-domain OSINT telemetry from 60+ live intelligence feeds into a single dark-ops map interface. Key features include 35+ toggleable data layers, multiple visual modes, and an obfuscated communications protocol.
Next.js, MapLibre GL, FastAPI, and Python power this platform.
Designed for analysts, researchers, and anyone curious about global telemetry, ShadowBroker combines public datasets into a single interface, with no user data collected or transmitted. The project includes an optional Shodan connector and supports Meshtastic mesh radio nodes and APRS amateur radio networks.
Usage is straightforward: clone the repository, pull the Docker images, and run the container. docker compose up -d starts the platform, and http://localhost:3000 provides access to the dashboard.
Technical highlights include a modular architecture, security context, and ingress readiness for high-availability deployments. An experimental testnet offers decentralized intelligence mesh and Sovereign Shell governance economy, but no privacy guarantee is provided.
ShadowBroker is perfect for those who want to see what the world looks like when every public signal is on the same map. One platform to track them all - that's the power of ShadowBroker.
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🧠 Channel: https://t.me/GithubRe13 248
📌 Spotted on GitHub Trending: Anil-matcha/Open-Generative-AI — let's break it down.
🔗 https://github.com/Anil-matcha/Open-Generative-AI
📝 Open-source alternative to AI video platforms — Free AI image & video generation studio with 200+ models (Flux, Midjourney, Kling, Sora, Veo). No content filters. Self-hosted, MIT licensed.
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Open Generative AI is a free, open-source AI image, video, cinema, and lip sync studio that brings creative workflows to everyone. It supports text-to-image, image-to-image, text-to-video, image-to-video, and audio-driven lip sync generation across 200+ state-of-the-art models, all from a sleek, modern interface you can self-host and customize.
Key features include no content filters, no prompt rejections, and no subscription fees. The platform is extensible, allowing you to add your own models, modify the UI, and build on top of it.
For usage, you can try it online with no install required, or download the desktop app for macOS, Windows, or Linux. The desktop app supports two independent local engines: sd.cpp and Wan2GP, which can be used for image and video generation.
From a technical standpoint, the platform uses
sd.cpp for local model inference on the desktop app, and Wan2GP for remote server-based inference. It also supports Metal GPU acceleration on Apple Silicon.
The target audience includes anyone interested in generative AI, from artists and designers to developers and researchers.
In summary, Open Generative AI is a powerful, flexible, and free platform for creative workflows - unleash your imagination and generate anything.
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🧠 Channel: https://t.me/GithubRe13 248
🔍 Deep-diving into oven-sh/bun — fresh off the trending list.
🔗 https://github.com/oven-sh/bun
📝 Incredibly fast JavaScript runtime, bundler, test runner, and package manager – all in one
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Bun is an all-in-one toolkit for JavaScript and TypeScript apps, designed as a drop-in replacement for Node.js. It ships as a single executable called
bun. The Bun runtime is a fast JavaScript runtime written in Zig, powered by JavaScriptCore, reducing startup times and memory usage.
Key features include a test runner, script runner, and Node.js-compatible package manager. bun can run TypeScript and JSX out-of-the-box, and its built-in tools are significantly faster than existing options.
Usage examples include running tests with bun test, running scripts with bun run, and installing packages with bun install.
From a technical standpoint, Bun supports Linux, macOS, and Windows, and can be installed using a script, npm, or Homebrew. It automatically releases a canary build on every commit to main.
The target audience for Bun is JavaScript and TypeScript developers looking for a faster and more efficient alternative to Node.js.
In short, Bun is a game-changer for JavaScript development - it's like Node.js, but faster.
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🧠 Channel: https://t.me/GithubRe13 248
💡 calcom/cal.diy just hit the trending charts — here's why it matters.
🔗 https://github.com/calcom/cal.diy
📝 Scheduling infrastructure for absolutely everyone.
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Introduction to Cal.diy: Cal.diy is the community-driven, open-source scheduling platform, a fork of Cal.com with all enterprise/commercial code removed. It's designed for individuals and self-hosters who want full control over their scheduling infrastructure without any commercial dependencies.
Key Features:
- 100% MIT-licensed with no proprietary "Enterprise Edition" features
- No license key required, everything works out of the box
- Community-maintained, contributions are welcome
- Built with Next.js, tRPC, React.js, Tailwind CSS, Prisma.io, and Daily.co
Usage:
To get started, clone the repo, install packages with yarn, set up your .env file, and configure Node. You can use the quick start with `yarn dx` or manual setup with PostgreSQL.
Technical Highlights:
- Self-hosted project, no hosted/managed version
- Requires advanced knowledge of server administration, database management, and securing sensitive data
- Uses Docker and Docker Compose for local development
Audience:
Cal.diy is intended for personal, non-production use, and is strictly recommended for users who are comfortable with self-hosting and have advanced knowledge of server administration and database management.
Takeaway: With Cal.diy, you have full control over your scheduling infrastructure, but be prepared to take on the responsibilities of self-hosting and maintenance.
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🧠 Channel: https://t.me/GithubRe13 248
🎯 HKUDS/CLI-Anything landed on trending. Worth a proper look.
🔗 https://github.com/HKUDS/CLI-Anything
📝 "CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub:https://clianything.cc/
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Introducing CLI-Anything, a game-changer for making any software agent-native. The purpose of CLI-Anything is to bridge the gap between AI agents and the world's software, enabling agents to interact with various applications seamlessly.
Key Features:
-
CLI-Hub: a central registry for browsing, searching, and installing CLIs with a single pip command
- Support for multiple AI coding agents, including Claude Code, Pi, OpenClaw, and more
- Structured and composable text commands for complex workflows
- Lightweight and universal with minimal overhead, working across all systems without dependencies
Usage: Simply install the cli-anything-hub package using pip, then use the cli-hub command to browse, install, and manage CLIs.
Technical Highlights:
- Python 3.10+ support
- Self-describing CLIs with automatic documentation via --help flags
- Deterministic and reliable results for predictable agent behavior
Audience: Developers, AI researchers, and anyone interested in making software agent-native.
In summary, CLI-Anything is a powerful tool for bridging the gap between AI agents and software, and its agent-first design makes it an ideal choice for those looking to create seamless interactions between humans and agents.
With CLI-Anything, the future of human-AI collaboration is just one command line away.
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🧠 Channel: https://t.me/GithubRe
13 248
🚀 Meet tinyhumansai/openhuman: a gem from today's GitHub trending list.
🔗 https://github.com/tinyhumansai/openhuman
📝 Your Personal AI super intelligence. Private, Simple and extremely powerful.
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Meet OpenHuman, your personal AI super intelligence designed to integrate with you in your daily life. This open-source agentic assistant is private, simple, and extremely powerful. With a
clean desktop experience and short onboarding paths, you can get started in just a few clicks.
Key features include 118+ third-party integrations with one-click OAuth, a Memory Tree that stores your data locally, and auto-fetch that pulls fresh data into your memory tree every 20 minutes. You also get batteries included with web search, a web-fetch scraper, a full coder toolset, and native voice capabilities.
To get started, you can either download from the website or run the installation script in your terminal. The project is currently in early beta and is under active development, so expect some rough edges.
OpenHuman is perfect for anyone looking for a simple and powerful AI assistant that can integrate with their daily life. Whether you're a developer, a business user, or just someone looking for a new way to interact with AI, OpenHuman is definitely worth checking out.
In short, OpenHuman is revolutionizing the way we interact with AI, and with its user-centric approach and cutting-edge technology, it's an AI assistant that truly puts the user first - your new AI sidekick is just a click away.
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🧠 Channel: https://t.me/GithubRe
13 248
🔍 Deep-diving into colbymchenry/codegraph — fresh off the trending list.
🔗 https://github.com/colbymchenry/codegraph
📝 Pre-indexed code knowledge graph for Claude Code — fewer tokens, fewer tool calls, 100% local
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Supercharge your coding experience with CodeGraph, a semantic code intelligence tool that enhances Claude Code. Key features include smart context building, full-text search, impact analysis, and framework-aware routes, supporting
19+ languages.
To get started, run the installer with npx @colbymchenry/codegraph, then initialize your project with codegraph init -i. This sets up a local knowledge graph that enables faster and smarter code exploration, with 94% fewer tool calls and 77% faster exploration on average.
Technical highlights include a SQLite database, file watcher with native OS events, and support for web-framework routing files. CodeGraph is designed for developers and teams looking to improve their coding efficiency and collaboration.
Takeaway: CodeGraph is a game-changer for coding productivity, providing a 100% local solution that's both powerful and easy to use.
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🧠 Channel: https://t.me/GithubRe
13 248
📌 Spotted on GitHub Trending: pranshuparmar/witr — let's break it down.
🔗 https://github.com/pranshuparmar/witr
📝 Why is this running?
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witr is a tool that answers the question "Why is this running?" by explaining where a running process came from, how it was started, and what chain of systems is responsible for it existing. It provides a human-readable output or an interactive TUI dashboard. The tool is distributed as a single static binary for Linux, macOS, FreeBSD, and Windows, and can be installed via various package managers, such as
Homebrew, Conda, and Winget. witr is designed for system administrators, developers, and power users who need to understand the causality behind running processes. With witr, you can easily identify the root cause of a running process and take necessary actions. Get to the root of the matter with witr - it's like having a superpower for your system debugging!
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🧠 Channel: https://t.me/GithubRe