Github Top Repositories

⚡ 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 ────────────────────────────── 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. ────────────────────────────── 🧠 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 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. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 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. ────────────────────────────── 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. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 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. ────────────────────────────── 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。 ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🔍 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. ────────────────────────────── 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. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 lfnovo/open-notebook just hit the trending charts — here's why it matters. 🔗 https://github.com/lfnovo/open-notebook 📝 An Open Source implementation of Notebook LM with more flexibility and features ────────────────────────────── Welcome to Open Notebook, a private, multi-model, 100% local, full-featured alternative to Notebook LM. This platform empowers you to control your data, choose your AI models, and organize multi-modal content. With support for 18+ AI providers, including OpenAI, Anthropic, and Ollama, you can generate professional podcasts, search intelligently, and chat with context. Key Features include privacy-first design, multi-notebook organization, and universal content support. The platform also offers advanced podcast generation, intelligent search, and context-aware chat. To get started, simply download the docker-compose.yml file, set your encryption key, and start the services. Then, configure your AI provider and you're ready to create your first notebook. Open Notebook is perfect for researchers, students, and professionals who value data privacy and customization. With its comprehensive REST API and optional password protection, you can integrate Open Notebook into your existing workflow. In short, Open Notebook is the ultimate tool for anyone looking for a private, customizable, and powerful research platform. Take control of your data and unlock your full potential with Open Notebook. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 CopilotKit/CopilotKit is trending — and it deserves your attention. 🔗 https://github.com/CopilotKit/CopilotKit 📝 The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol ────────────────────────────── CopilotKit is a best-in-class SDK for building full-stack agentic applications, Generative UI, and chat applications. The key features include Chat UI, Backend Tool Rendering, Generative UI, Shared State, and Human-in-the-Loop workflows. To get started, you can use the npx copilotkit@latest create -f <framework> command for new projects or npx copilotkit@latest init for existing projects. The useAgent hook provides a superset of useCoAgent and offers more control over the agent connection. The Generative UI pattern allows agents to dynamically render UI as part of their workflow. With a strong focus on community and documentation, CopilotKit is perfect for developers looking to build cutting-edge applications. You can install it as a Claude Code plugin and explore the various skills and lifecycle journey skills. One-liner takeaway: CopilotKit is revolutionizing the way we build agentic applications, and you can get started in just one minute! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 chopratejas/headroom landed on trending. Worth a proper look. 🔗 https://github.com/chopratejas/headroom 📝 Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. ────────────────────────────── Headroom is a context compression layer for AI agents that reduces the number of tokens sent to language models, resulting in significant savings. It achieves this through a combination of library, proxy, and agent wrap modes. Key features include cross-agent memory, reversible compression, and support for multiple algorithms. Technical highlights include the use of SmartCrusher for JSON compression, CodeCompressor for AST-aware compression, and Kompress-base for text compression. The CacheAligner ensures that provider KV caches are utilized effectively. Headroom is suitable for developers and researchers working with AI agents, particularly those who need to reduce the token count for their models. It supports various agents, including Claude, Codex, and Cursor, and can be integrated into existing workflows using the provided SDKs and APIs. To get started, simply install headroom-ai using pip or npm and follow the documentation for your specific use case. In summary, Headroom is a powerful tool for reducing token count in AI agent workflows, and its flexible architecture makes it easy to integrate into existing projects. With Headroom, you can compress everything, sacrifice nothing. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 NousResearch/hermes-agent caught my eye on GitHub Trending today. 🔗 https://github.com/NousResearch/hermes-agent 📝 The agent that grows with you ────────────────────────────── Hermes Agent is a self-improving AI agent built by Nous Research, designed to learn from experience and improve over time. It features a closed learning loop, allowing it to create skills from experience, improve them during use, and search its own past conversations. The agent can be run on a variety of platforms, including a $5 VPS, a GPU cluster, or serverless infrastructure, and can be accessed from Telegram, Discord, Slack, WhatsApp, Signal, or the command line. Key features include: - A real terminal interface with multiline editing, slash-command autocomplete, and conversation history - The ability to live where you do, with support for multiple messaging platforms - A closed learning loop with agent-curated memory and periodic nudges - Scheduled automations with a built-in cron scheduler - The ability to delegate and parallelize tasks using isolated subagents To get started, you can install Hermes Agent using a simple one-liner command, and then configure it using the hermes setup command. The agent supports a wide range of models and providers, including Nous Portal, OpenRouter, and Hugging Face. Technical highlights include support for multiple terminal backends, a research-ready architecture, and a scalable design that allows it to run on a variety of hardware configurations. The target audience for Hermes Agent includes developers, researchers, and anyone interested in building and interacting with AI agents. In summary, Hermes Agent is a powerful and flexible AI agent that can be used for a wide range of applications, from research and development to personal productivity and automation - it's an AI agent that learns and adapts to your needs. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 mvanhorn/last30days-skill is trending — and it deserves your attention. 🔗 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 ────────────────────────────── Introducing the /last30days-skill GitHub repository, a game-changing AI-powered search engine that aggregates information from various sources, including Reddit, X, YouTube, TikTok, and GitHub. This innovative tool scores results based on upvotes, likes, and real money, providing a more accurate and unbiased view of what's currently trending. Key features include a zero-config setup, immediate access to various platforms, and the ability to unlock additional sources with a simple setup wizard. The engine also features intelligent search, best takes, cross-source cluster merging, single-pass comparisons, and auto-discovered competitor comparisons. /last30days can be used in various ways, such as before a meeting to gather information about a person or company, when something drops to stay up-to-date on the latest news, or to compare tools and understand the world. Technical highlights include a Python pre-research brain that resolves topics and searches the right people and communities, a second judge that scores results for humor and virality, and a cross-source cluster merging feature that combines similar stories from different platforms. Audience includes anyone looking for a more accurate and comprehensive search engine, such as professionals, researchers, and individuals seeking to stay informed about current events. To get started, simply install the last30days-skill using Claude Code or other supported platforms, and begin searching with the /last30days command. In conclusion, /last30days-skill is a revolutionary search engine that provides a more accurate and unbiased view of what's currently trending, making it an essential tool for anyone seeking to stay informed in today's fast-paced world: Stay ahead of the curve with /last30days-skill, the ultimate AI-powered search engine. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 reconurge/flowsint is trending — and it deserves your attention. 🔗 https://github.com/reconurge/flowsint 📝 A modern platform for visual, flexible, and extensible graph-based investigations. For cybersecurity analysts and investigators. ────────────────────────────── Introduction to Flowsint: Flowsint is an open-source OSINT graph exploration tool designed for ethical investigation, transparency, and verification. It's built to help users explore relationships between entities through a visual graph interface and automated enrichers. Key Features: - Graph-based investigation - Automated enrichers for domains, IPs, social media, and more - Support for multiple data types, including domains, IPs, ASNs, and more - Modern and user-friendly interface Usage: To get started, users can install Flowsint using Docker and Make on Linux/macOS or using Docker Desktop on Windows. The application is accessible at http://localhost:5173. Technical Highlights: - Modular structure with separate modules for core utilities, enrichers, API, and frontend - Built using Python, FastAPI, and Pydantic - Supports PostgreSQL and Neo4j databases Audience: Flowsint is designed for cybersecurity researchers, journalists, law enforcement, and organizations conducting internal threat intelligence or digital risk analysis. Important Note: Flowsint is strictly for lawful, ethical investigation and research purposes. Any misuse of this software is prohibited. In short, Flowsint is a powerful tool for OSINT investigations - use it to uncover hidden connections, and always remember: with great power comes great responsibility. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe