Github Top Repositories

📌 Spotted on GitHub Trending: mvanhorn/last30days-skill — let's break it down. 🔗 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 ────────────────────────────── Last30Days Skill is a revolutionary search engine that uses AI to synthesize information from various sources like Reddit, X, YouTube, and GitHub, scoring it by what real people engage with, not editors. It's like having a superpower that helps you stay up-to-date on the latest developments in any field. To use it, simply type /last30days [topic] and the AI agent will search all relevant sources in parallel, synthesizing the information into a brief. No more tedious searching or outdated information. The skill has many features, including shareable HTML briefs, intelligent search that understands your topic before searching, and cross-source cluster merging that combines similar stories from different sources. It's perfect for researchers, entrepreneurs, and anyone who wants to stay informed. Whether you're looking for information on a person, company, or topic, Last30Days Skill is the ultimate tool for you. With its ability to search multiple sources at once and synthesize the information into a concise brief, Last30Days Skill is an indispensable tool for anyone looking to stay ahead of the curve. Get the latest scoop in seconds, not hours. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 github/copilot-sdk is trending — and it deserves your attention. 🔗 https://github.com/github/copilot-sdk 📝 Multi-platform SDK for integrating GitHub Copilot Agent into apps and services ────────────────────────────── The Github Copilot SDK is a set of APIs that allows you to integrate the capabilities of Github Copilot into your own applications. With this SDK, you can embed Copilot's agentic workflows into your app and invoke them programmatically. The SDK exposes the same engine as the Copilot CLI, handling planning, tool invocation, and file edits. The SDK supports multiple programming languages, including Node.js/TypeScript, Python, Go, .NET, Java, and Rust. You can install the SDK using the respective package managers, such as npm install @github/copilot-sdk for Node.js or pip install github-copilot-sdk for Python. To get started, you can follow the Getting Started Guide, which provides a walkthrough of the installation and usage process. The SDK also provides a range of features, including support for custom agents, skills, and tools, as well as BYOK (Bring Your Own Key) for using your own API keys. The SDK is designed to be production-ready and follows semantic versioning. If you encounter any issues or have feature requests, you can report them on the Github Issues page. In summary, the Github Copilot SDK is a powerful tool for integrating Copilot's capabilities into your own applications, with support for multiple programming languages and a range of features. With this SDK, you can unlock the full potential of Copilot and take your development to the next level. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: jwasham/coding-interview-university — let's break it down. 🔗 https://github.com/jwasham/coding-interview-university 📝 A complete computer science study plan to become a software engineer. ────────────────────────────── Coding Interview University is a comprehensive study plan to help you prepare for a technical interview at top software companies like Amazon, Facebook, Google, and Microsoft. Created by John Washam, this plan covers the essential topics you need to know, from data structures and algorithms to system design and scalability. To get started, choose a programming language and begin with the basics, such as variables, loops, and methods. The plan includes a daily study schedule and practice coding questions to help you stay on track. Key features of this plan include: - Step-by-step learning: Break down complex topics into manageable chunks - Practice coding questions: Reinforce your understanding with hands-on exercises - Study schedule: Stay organized and focused with a daily plan Technical highlights of this plan include: - Algorithmic complexity: Understand Big-O notation and asymptotic analysis - Data structures: Learn about arrays, linked lists, stacks, queues, and hash tables - System design: Study scalability, data handling, and system architecture This plan is designed for anyone looking to improve their coding skills, from beginners to experienced engineers. Don't be intimidated if you're new to coding - this plan will guide you through the process. In short, Coding Interview University is your one-stop resource for preparing for technical interviews. With dedication and practice, you'll be well on your way to landing your dream job - so start coding and crush that interview! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🚀 Meet aquasecurity/trivy: a gem from today's GitHub trending list. 🔗 https://github.com/aquasecurity/trivy 📝 Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more ────────────────────────────── Trivy is a versatile security scanner that detects vulnerabilities, misconfigurations, and secrets in various targets, including container images, filesystems, and Kubernetes. Its scanners can identify issues such as OS packages, software dependencies, and sensitive information. trivy supports multiple programming languages, operating systems, and platforms. To get started, you can install Trivy using brew install trivy or docker run aquasec/trivy, then use the trivy command to scan your target, like trivy image python:3.4-alpine or trivy fs --scanners vuln,secret,misconfig myproject/. Trivy is designed for developers, security teams, and DevOps engineers who want to ensure the security and integrity of their systems. With its extensive features and integrations, Trivy is a powerful tool for anyone looking to strengthen their security posture - and that's a trivy worth trying! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ openclaw/openclaw-windows-node is making waves. Here's the full picture. 🔗 https://github.com/openclaw/openclaw-windows-node 📝 Windows companion suite for OpenClaw - System Tray app, Shared library, Node, and PowerToys Command Palette extension ────────────────────────────── The openclaw-windows-node repository is a native Windows companion suite for OpenClaw, an AI-powered personal assistant. This monorepo contains the Windows hub, shared client libraries, and CLI utilities. Key features include a system tray application with a modern UI, quick send functionality via global hotkey, and auto-updates from GitHub Releases. To use, simply download the latest stable installer, or build from source using the provided build.ps1 script. Technical highlights include support for Windows 10 and 11, .NET 10.0 SDK, and WebView2 Runtime. The repository also includes a CLI validator for testing gateway connectivity and WebSocket send/probe functionality. The target audience is developers and users of the OpenClaw AI assistant who want a native Windows experience. In a nutshell, openclaw-windows-node brings the power of OpenClaw to Windows, with a sleek and modern interface, and a robust set of features that make it an ideal companion for anyone looking to take their productivity to the next level - so why not claw your way to the top with OpenClaw on Windows? ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🔥 withastro/flue is trending — and it deserves your attention. 🔗 https://github.com/withastro/flue 📝 The sandbox agent framework. ────────────────────────────── Flue is The Agent Harness Framework, a TypeScript framework for building the next generation of agents, designed around a built-in agent harness. It allows you to create autonomous agents that can solve problems and complete tasks with minimal code, using Markdown for skills, context, and configuration. Key features include a runtime-agnostic framework, allowing deployment on various platforms such as Node.js, Cloudflare, and GitHub Actions. The framework provides a virtual sandbox for faster and more scalable agent execution, as well as support for container-based sandboxes for more complex environments. To use Flue, you can create an agent by importing the necessary modules and defining a workflow handler, which orchestrates the agent's actions. You can also use the flue CLI to build, run, and deploy your agents. Flue is suitable for developers and teams looking to build autonomous agents that can interact with various systems and services. It provides a flexible and extensible framework for creating customized agents that can be integrated into different applications and workflows. One-liner takeaway: Flue empowers you to build autonomous agents that can run anywhere, interact with anything, and learn from everything. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ MemPalace/mempalace is making waves. Here's the full picture. 🔗 https://github.com/MemPalace/mempalace 📝 The best-benchmarked open-source AI memory system. And it's free. ────────────────────────────── MemPalace is a local-first AI memory solution that stores conversation history as verbatim text and retrieves it with semantic search. It features a pluggable backend, with ChromaDB as the default, and supports alternative backends like SQLite, Qdrant, and Postgres. Key highlights include zero API calls, a temporal entity-relationship graph, and support for MCP tools and agents. mempalace can be installed using uv tool install or pipx install, and a Docker image is also available. The project provides a CLI for mining content, searching, and loading context, with a quickstart guide available. Benchmarks demonstrate high retrieval recall rates, including 96.6% R@5 on LongMemEval. Technical requirements include Python 3.9+, a vector-store backend, and approximately 300 MB disk space for the embedding model. The target audience appears to be developers and users interested in local-first AI memory solutions, with a focus on those already familiar with tools like Claude Code. In short, MemPalace is a powerful tool for local-first AI memory, and its flexibility and customizability make it an attractive choice for those seeking a robust and private solution - take control of your memories with MemPalace, where your data stays local and private. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet openai/plugins: a gem from today's GitHub trending list. 🔗 https://github.com/openai/plugins 📝 OpenAI Plugins ────────────────────────────── The openai/plugins repository is a treasure trove of Codex plugin examples, each with its own unique features and use cases. At its core, the repository contains a collection of plugins, each living in its own directory with a plugin.json manifest file. You'll find a range of plugins, from figma and notion to build-ios-apps and build-web-apps, each with its own set of capabilities and companion files. Whether you're looking to automate tasks, streamline workflows, or just explore the possibilities of Codex, this repository has something for you. With its diverse range of plugins and examples, it's perfect for developers, power users, and anyone looking to get the most out of Codex. Dive in and discover the power of plugins - your automation possibilities just got a whole lot bigger! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet PaddlePaddle/PaddleOCR: a gem from today's GitHub trending list. 🔗 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. ────────────────────────────── PaddleOCR is a leading OCR toolkit and document AI engine that converts PDF documents and images into structured data with high accuracy. Its key features include intelligent document parsing, universal text recognition, and a developer-centric ecosystem. The PaddleOCR-VL-1.6 model achieves 96.3% accuracy on OmniDocBench v1.6 and supports 100+ languages. The toolkit is designed for production-ready efficiency and is trusted by top-tier projects. With 70k+ Stars and a strong community, PaddleOCR is the go-to choice for building intelligent applications. Get started with PaddleOCR today and unlock the power of document AI. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 mvanhorn/last30days-skill just hit the trending charts — here's why it matters. 🔗 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 ────────────────────────────── Discover the power of /last30days, an AI agent-led search engine that scores results based on upvotes, likes, and real money, not editors. This innovative tool allows you to search across various platforms, including Reddit, X, YouTube, TikTok, and more, all in parallel. With its zero-config setup, you can unlock a world of information, from what people are actually doing this month to the latest news and trends. Key features include: * /last30days command to search for any topic * Support for multiple platforms, including Reddit, X, YouTube, TikTok, and more * Scoring based on upvotes, likes, and real money * --emit=html option to generate shareable HTML briefs Technical highlights include: * Python pre-research brain to resolve topics and search the right people and communities * Entity-based overlap detection to merge similar stories from different platforms * Single-pass comparisons for faster and more efficient searches Audience: Anyone looking to stay up-to-date on the latest news and trends, from business professionals to individuals interested in technology and innovation. In short, /last30days is a game-changer for searching and discovering new information - it's like having a superpower in your pocket! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 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 ────────────────────────────── MiroFish is a next-generation AI prediction engine that utilizes multi-agent technology to create a high-fidelity parallel digital world. This world is constructed by extracting seed information from the real world, such as news or financial signals, and then thousands of intelligent agents interact and evolve within it. The engine allows users to inject variables and deduce future trajectories through countless simulations. Key features include a simple and universal swarm intelligence engine, the ability to predict anything, and a creative sandbox for users. The engine is powered by OASIS (Open Agent Social Interaction Simulations) and has received strategic support from Shanda Group. To get started, users can deploy the engine via source code or Docker, with options for frontend and backend installation. The engine can be used for various applications, including financial prediction, political news prediction, and more. The target audience for MiroFish includes decision-makers, individual users, and anyone interested in multi-agent simulation and LLM applications. With MiroFish, you can rehearse the future in a digital sandbox and make informed decisions after simulating countless scenarios - making it possible to predict anything, one simulation at a time. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 NVIDIA/cosmos just hit the trending charts — here's why it matters. 🔗 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. ────────────────────────────── NVIDIA Cosmos is an open platform for building Physical AI, providing a suite of omnimodal world models, datasets, and tools. The Cosmos 3 model family is designed to jointly process and generate language, images, video, audio, and action sequences within a unified Mixture-of-Transformers architecture. Key features include world understanding, world generation, and action modeling. The platform supports various input and output formats, such as text, images, videos, and JSON action arrays. To get started, users can create a Hugging Face access token, authenticate locally, and set up a virtual environment using uvx and hf commands. The platform provides examples for both Generator and Reasoner modes, including text-to-image, text-to-video, and video-to-video generation, as well as captioning, temporal localization, and embodied reasoning. The takeaway: NVIDIA Cosmos is a powerful tool for building Physical AI applications, offering a flexible and scalable platform for researchers and developers to create innovative solutions. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe