Github Top Repositories
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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Show more📈 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 14 268 subscribers, ranking 13 983 in the Education category and 28 170 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 14 268 subscribers.
According to the latest data from 05 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 255 over the last 30 days and by 8 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 0.92%. Within the first 24 hours after publication, content typically collects 0.61% reactions from the total number of subscribers.
- Post reach: On average, each post receives 131 views. Within the first day, a publication typically gains 87 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.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Thanks to the high frequency of updates (latest data received on 06 September, 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.
14 268
Subscribers
+824 hours
+1197 days
+25530 days
Posts Archive
14 265
🎯 HKUDS/Vibe-Trading landed on trending. Worth a proper look.
🔗 https://github.com/HKUDS/Vibe-Trading
📝 "Vibe-Trading: Your Personal Trading Agent"
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Vibe-Trading is your personal trading agent, empowering you with comprehensive trading capabilities through one command. This project features a
connector-first trading layer with support for multiple brokers, including IBKR, Robinhood, and OKX. The FastAPI backend and React frontend provide a robust and user-friendly interface.
Key features include paper trading, read-only account access, and bounded autonomy with a user-committed mandate. The project is written in Python 3.11+ and is available on PyPI.
The target audience includes traders, investors, and developers interested in building custom trading strategies. To get started, simply run pip install vibe-trading-ai and explore the website and docs for more information.
With Vibe-Trading, automate your trading decisions and take your investments to the next level - trade smart, not hard.
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🧠 Channel: https://t.me/GithubRe
14 265
⚡ aquasecurity/trivy is making waves. Here's the full picture.
🔗 https://github.com/aquasecurity/trivy
📝 Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more
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Trivy is a comprehensive security scanner that can detect various security issues in different targets, including container images, file systems, Git repositories, virtual machine images, and Kubernetes. It has multiple scanners that look for known vulnerabilities, configuration issues, sensitive information, and software licenses.
To use Trivy, you can install it using popular package managers like
brew or download the binary from the GitHub releases page. Trivy also has a GitHub Actions integration and a Kubernetes operator.
Here's a basic example of how to use Trivy:
trivy image python:3.4-alpine
14 265
🔥 openclaw/openclaw-windows-node is trending — and it deserves your attention.
🔗 https://github.com/openclaw/openclaw-windows-node
📝 Windows companion suite for OpenClaw - System Tray app, Shared library, Node, and PowerToys Command Palette extension
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The OpenClaw Windows Node is an open-source, native Windows companion suite for OpenClaw, an AI-powered personal assistant. It's designed to work seamlessly with the OpenClaw gateway, providing a system tray application, shared client libraries, and CLI utilities.
Key features include a modern Windows 11-style system tray companion with dark/light mode support, quick send functionality via global hotkey, auto-updates, and embedded web chat. The suite also offers a command center with diagnostics, channel health, usage, sessions, nodes, and copyable repair commands.
To get started, users can download the latest stable installer from the OpenClaw Windows docs or build the project using the provided build script. The project requires Windows 10 (20H2+) or Windows 11, .NET 10.0 SDK, Windows 10 SDK, and WebView2 Runtime.
The OpenClaw Windows Node is designed for users who want a seamless and integrated experience with their OpenClaw gateway. With its robust feature set and user-friendly interface, it's an ideal choice for anyone looking to enhance their productivity and streamline their workflow.
One-liner takeaway:
OpenClaw Windows Node is the ultimate Windows companion for OpenClaw users, offering a powerful and intuitive system tray application that simplifies your workflow and boosts productivity!
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🧠 Channel: https://t.me/GithubRe
14 265
🔥 MemPalace/mempalace is trending — and it deserves your attention.
🔗 https://github.com/MemPalace/mempalace
📝 The best-benchmarked open-source AI memory system. And it's free.
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Introduction to MemPalace: MemPalace is a local-first AI memory tool that stores conversation history as verbatim text and retrieves it with semantic search. It's designed to be private and secure, with no API calls or cloud dependencies.
Main Features:
- Verbatim storage of conversation history
- Semantic search for retrieving stored conversations
- Pluggable backend for flexibility
- Local-first approach for privacy and security
- CLI and Python API for easy usage
Usage Example:
```bash
mempalace mine ~/projects/myapp # mine project files
mempalace mine ~/.claude/projects/ --mode convos # mine Claude Code sessions
mempalace search "why did we switch to GraphQL" # search conversations
```
Technical Highlights:
- 96.6% retrieval recall on LongMemEval benchmark
- Pluggable backend with ChromaDB as the default
- Support for multiple languages
Audience: MemPalace is suitable for developers, researchers, and anyone looking for a private and secure way to store and retrieve conversation history.
Takeaway: MemPalace is a powerful tool for storing and retrieving conversation history, with a strong focus on privacy and security, making it an excellent choice for those who value their data.
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🧠 Channel: https://t.me/GithubRe14 265
🔍 Deep-diving into openai/plugins — fresh off the trending list.
🔗 https://github.com/openai/plugins
📝 OpenAI Plugins
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The openai/plugins repository is a treasure trove of curated Codex plugin examples. Each plugin is neatly organized under its own directory, complete with a required
.codex-plugin/plugin.json manifest file and optional supporting files like skills/, .app.json, and agents/.
Some of the highlighted plugins include figma for design system rules, notion for planning and knowledge capture, and build-ios-apps for SwiftUI implementation and debugging.
To get started, simply explore the various plugins, such as expo, netlify, and google-slides, and discover how they can streamline your workflow.
Whether you're a developer, designer, or researcher, this repository has something for everyone.
The openai/plugins repo is a game-changer - and the best part is, you can plug and play your way to productivity!
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🧠 Channel: https://t.me/GithubRe14 265
🌟 PaddlePaddle/PaddleOCR caught my eye on GitHub Trending today.
🔗 https://github.com/PaddlePaddle/PaddleOCR
📝 Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
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PaddleOCR is a leading OCR toolkit and document AI engine that converts PDF documents and images into structured, LLM-ready data with industry-leading accuracy. It features intelligent document parsing, universal text recognition, and a developer-centric ecosystem. With
70k+ Stars and trusted by top-tier projects, PaddleOCR is the bedrock for building intelligent RAG and Agentic applications.
Key features include SOTA Document VLM with 96.3% accuracy on OmniDocBench v1.6, structure-aware conversion to Markdown or JSON, and universal text recognition supporting 100+ languages.
It's designed for production-ready efficiency, achieving commercial-grade accuracy with an ultra-small footprint, and is seamlessly integrated with the Hugging Face ecosystem.
Whether you're a developer or researcher, PaddleOCR provides a complete pipeline to build high-quality datasets and supports various hardware backends.
One-liner takeaway: PaddleOCR simplifies document parsing and text recognition, empowering you to build intelligent applications with ease and accuracy!
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🧠 Channel: https://t.me/GithubRe
14 265
⚡ mvanhorn/last30days-skill is making waves. Here's the full picture.
🔗 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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The mvanhorn/last30days-skill GitHub repository is home to a revolutionary AI agent-led search engine. This engine scores results based on upvotes, likes, and real money, rather than editor opinions. Key features include zero-config setup, immediate functionality with Reddit, HN, Polymarket, and GitHub, and the ability to unlock more platforms like X, YouTube, and TikTok in just 30 seconds.
Technical highlights of this repository include the use of a
pre-research brain built in Python, which resolves topics and figures out where to search before the search begins. The engine also features intelligent search, cross-source cluster merging, and single-pass comparisons, making it a powerful tool for finding relevant information.
This repository is perfect for anyone looking to stay up-to-date on the latest developments in their field, including developers, researchers, and industry professionals. With its ability to search multiple platforms at once and provide a brief summary of the most relevant information, mvanhorn/last30days-skill is an invaluable resource.
To get started, users can install the skill using /plugin marketplace add mvanhorn/last30days-skill or npx skills add mvanhorn/last30days-skill -g. The repository is constantly being updated with new features and improvements, making it an exciting project to follow.
One-liner takeaway: mvanhorn/last30days-skill is a game-changing search engine that uses AI to scour multiple platforms and provide you with the most relevant, up-to-date information on any topic.
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🧠 Channel: https://t.me/GithubRe14 265
🌟 666ghj/MiroFish caught my eye on GitHub Trending today.
🔗 https://github.com/666ghj/MiroFish
📝 A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
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MiroFish is a cutting-edge AI prediction engine that utilizes multi-agent technology to forecast outcomes. By analyzing real-world data, it creates a parallel digital world where thousands of intelligent agents interact and evolve. This allows users to rehearse the future in a digital sandbox and make informed decisions after simulating various scenarios.
Key features include:
-
Graph Building: extracting seed information and constructing a high-fidelity digital world
- Simulation: running parallel simulations to predict future trajectories
- Report Generation: generating detailed prediction reports
The workflow involves:
1. Graph building and environment setup
2. Simulation and report generation
3. Deep interaction with the simulated world
Technical highlights include:
- Utilization of OASIS (Open Agent Social Interaction Simulations) for the simulation engine
- Support for LLM API and Zep Cloud configurations
The target audience includes decision-makers, researchers, and individuals interested in exploring what if scenarios.
To get started, users can deploy MiroFish via source code or Docker, and join the conversation on social media platforms.
In a nutshell, MiroFish is all about predicting anything - from serious predictions to playful simulations, making it possible to rehearse the future and win decisions after countless simulations.
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🧠 Channel: https://t.me/GithubRe
14 265
📌 Spotted on GitHub Trending: NVIDIA/cosmos — let's break it down.
🔗 https://github.com/NVIDIA/cosmos
📝 NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.
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NVIDIA Cosmos is an open platform for building Physical AI, providing a suite of world models, datasets, and tools. Cosmos 3 is the latest model family, designed to jointly process and generate language, images, video, audio, and action sequences. It has two runtime surfaces:
Reasoner for world understanding and Generator for world generation.
Key features include:
- World understanding: analyze videos and images for captions, temporal events, and physical plausibility
- World generation: produce images, videos, sound, and action-conditioned rollouts from text, image, video, or action inputs
- Action modeling: predict policy actions for robotics and autonomous-driving settings
Cosmos 3 has a unified Mixture-of-Transformers architecture, combining an autoregressive transformer for reasoning with a diffusion transformer for multimodal generation. The model family includes Cosmos3-Nano, Cosmos3-Super, and specialized models for text-to-image and image-to-video generation.
To get started, create a Hugging Face access token, authenticate locally, and set up a virtual environment with the required dependencies. You can use HuggingFace Diffusers for research, training, and model development.
One-liner takeaway: NVIDIA Cosmos is revolutionizing Physical AI by providing a powerful platform for world understanding and generation, enabling developers to build more sophisticated robots, autonomous vehicles, and smart infrastructure.
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🧠 Channel: https://t.me/GithubRe
14 265
🔥 Panniantong/Agent-Reach is trending — and it deserves your attention.
🔗 https://github.com/Panniantong/Agent-Reach
📝 Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
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Agent Reach 是一个让 AI Agent 无缝访问各大网站和平台的工具，解决了 Agent 访问网页、YouTube、Twitter、Reddit、GitHub 等平台的痛点。它通过提供了一套简单的命令行工具，让 AI Agent 可以轻松地搜索、阅读和交互这些平台的内容。
主要特点：
* 支持多个平台，包括网页、YouTube、Twitter、Reddit、GitHub 等
* 提供简单的命令行工具，让 AI Agent 可以轻松地访问这些平台
* 自动配置和安装，方便用户使用
* 支持安全模式，确保用户的安全
安装命令：
```
帮我安装 Agent Reach：https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md
```
总结：Agent Reach 是一个简单却强大的工具，让 AI Agent 可以无缝访问各大网站和平台，解决了访问这些平台的痛点。通过提供简单的命令行工具和自动配置，Agent Reach 让用户可以轻松地使用这些平台。只要一行代码，你的 AI Agent 就可以成为一个全能的互联网助手。
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🧠 Channel: https://t.me/GithubRe
14 265
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14 265
🔍 Deep-diving into affaan-m/ECC — fresh off the trending list.
🔗 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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The ECC repository on GitHub is a harness-native operator system designed for agentic work. It's built from real-world multi-harness engineering workflows, offering a complete system with skills, instincts, memory optimization, continuous learning, security scanning, and research-first development.
The system works across various AI agent harnesses, including
Codex, Claude Code, Cursor, OpenCode, Gemini, Zed, and GitHub Copilot.
Key features include production-ready agents, skills, hooks, rules, and configurations, all of which have evolved over 10+ months of intensive daily use in building real products.
The repository has a large community with 182K+ stars, 28K+ forks, and 170+ contributors, making it a significant project in the open-source space.
The system is written in multiple programming languages, including Shell, TypeScript, Python, Go, Java, and Perl, and it supports 12+ language ecosystems.
To get started, users can refer to the Shorthand Guide, Longform Guide, and Security Guide for detailed information on setup, foundations, philosophy, token optimization, memory persistence, and security.
In summary, ECC is a powerful tool for agentic work, with a wide range of features, a large community, and support for multiple programming languages, making it an ideal choice for developers and operators alike.
The takeaway: ECC is the ultimate operator system for agentic work, empowering developers to build and manage complex workflows with ease.
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🧠 Channel: https://t.me/GithubRe