Github Top Repositories

📌 Spotted on GitHub Trending: obra/superpowers — let's break it down. 🔗 https://github.com/obra/superpowers 📝 An agentic skills framework & software development methodology that works. ────────────────────────────── Superpowers is a software development methodology for coding agents, built on composable skills and initial instructions. It enables agents to ask questions, create plans, and implement code in a systematic way. The key features include test-driven development, systematic debugging, and collaboration tools. Usage involves installing the plugin for your chosen coding agent, such as Claude Code or Codex CLI, and then following the workflow: brainstorming, using-git-worktrees, writing-plans, and executing-plans. Technical highlights include a skills library with testing, debugging, and collaboration skills, as well as a meta skill for creating new skills. The target audience is developers who want to improve their coding productivity and quality. The punchy one-liner takeaway: Superpowers turns your coding agent into a full-fledged development partner. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 K-Dense-AI/scientific-agent-skills just hit the trending charts — here's why it matters. 🔗 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. ────────────────────────────── The Scientific Agent Skills repository provides 135 ready-to-use scientific and research skills for any AI agent that supports the open Agent Skills standard. These skills enable your AI agent to seamlessly work with specialized scientific libraries, databases, and tools across multiple scientific domains. Key features include: - 100+ scientific and financial databases access - 70+ optimized Python package skills with curated documentation and examples - 9 scientific integration skills for platforms like Benchling and OMERO - 30+ analysis and communication tools for tasks like literature review and scientific writing Usage is straightforward: simply install the skills using npx or the GitHub CLI, and your AI agent will automatically discover and use them. Technical highlights include a unified database-lookup skill for accessing multiple databases and pre-documented, higher-performing paths for optimized Python packages. The target audience is researchers and scientists looking to transform their AI coding agent into an 'AI Scientist' capable of executing complex multi-step scientific workflows. One-liner takeaway: With Scientific Agent Skills, you can turn your AI agent into a powerful research assistant and accelerate your scientific discovery across biology, chemistry, medicine, and more. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 oven-sh/bun landed on trending. Worth a proper look. 🔗 https://github.com/oven-sh/bun 📝 Incredibly fast JavaScript runtime, bundler, test runner, and package manager – all in one ────────────────────────────── Bun is an all-in-one toolkit for JavaScript and TypeScript apps, designed as a drop-in replacement for Node.js. It features a fast JavaScript runtime, written in Zig and powered by JavaScriptCore, reducing startup times and memory usage. The bun command-line tool includes a test runner, script runner, and Node.js-compatible package manager. Key features include support for TS and JSX out-of-the-box, a built-in bun test runner, and a bun install package manager. It's easy to install on Linux, macOS, and Windows, with various methods available, including a simple curl script. The Bun toolkit is suitable for developers looking for a fast, efficient, and easy-to-use alternative to Node.js. With its extensive documentation and active community, Bun is a great choice for building and deploying JavaScript and TypeScript applications. In short, Bun is the ultimate toolkit for JavaScript and TypeScript developers, making it fast, easy, and fun to build and deploy apps - and that's a recipe for success! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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⚡ joeseesun/qiaomu-anything-to-notebooklm is making waves. Here's the full picture. 🔗 https://github.com/joeseesun/qiaomu-anything-to-notebooklm 📝 Claude Skill: Multi-source content processor for NotebookLM. Supports WeChat articles, web pages, YouTube, PDF, Markdown, search queries → Podcast/PPT/MindMap/Quiz etc. ────────────────────────────── Anything → NotebookLM 是一个强大的工具，能将任何内容转换为多种格式，如播客、PPT、思维导图、Quiz 等。它支持 15+ 种内容源，包括微信公众号、X/Twitter、YouTube 视频、播客、电子书、Office 文档等。 核心特性 包括自动识别内容源类型、自动调用对应工具、付费墙自动绕过、全自动处理等。它还支持混合多种内容源、深度分析模式、飞书文档输出等高级用法。 技术架构 包括 Claude Code Skill、NotebookLM API、MCP 工具、markitdown 文件转换等。 使用示例 包括付费文章转播客、播客转 PPT、电子书转深度分析等。 总的来说，Anything → NotebookLM 是一个非常有用的工具，可以帮助你快速将任何内容转换为多种格式，非常适合研究、学习、工作等场景。 结论：使用 Anything → NotebookLM，可以快速将任何内容转换为多种格式，节省时间，提高效率。 赶快试试吧！ ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🎯 mattpocock/skills landed on trending. Worth a proper look. 🔗 https://github.com/mattpocock/skills 📝 Skills for Real Engineers. Straight from my .claude directory. ────────────────────────────── The mattpocock/skills GitHub repository offers a collection of skills designed to enhance your workflow with coding agents. The purpose of these skills is to tackle common issues such as misalignment, verbosity, and poor code quality. Key features include grilling sessions to ensure you and the agent are on the same page, a shared language to reduce verbosity, and feedback loops to improve code quality. To get started, simply run the skills.sh installer and follow the prompts to set up the skills you want. The skills are designed to be small, easy to adapt, and composable, working with any model. Technical highlights include the use of npx skills@latest add mattpocock/skills for installation and the /setup-matt-pocock-skills command to configure your skills. These skills are suitable for developers and engineers looking to improve their workflow with coding agents. In short, mattpocock/skills helps you work better with coding agents - try it and supercharge your development workflow! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet oven-sh/bun: a gem from today's GitHub trending list. 🔗 https://github.com/oven-sh/bun 📝 Incredibly fast JavaScript runtime, bundler, test runner, and package manager – all in one ────────────────────────────── Bun is an all-in-one toolkit for JavaScript and TypeScript apps, designed to be a fast and efficient alternative to Node.js. At its core is the Bun runtime, which dramatically reduces startup times and memory usage. The bun command-line tool implements a test runner, script runner, and Node.js-compatible package manager, making it a great option for developers who want to simplify their workflow. With bun, you can run scripts, test your code, and install packages with ease. It also supports TSX and JSX out-of-the-box. The toolkit is highly customizable, with a wide range of plugins and configurations available. Technical highlights of Bun include its fast JavaScript runtime, written in Zig and powered by JavaScriptCore, as well as its Node.js compatibility. The toolkit is suitable for developers of all levels, from beginners to experienced professionals. To get started with Bun, you can install it using a simple curl command, and then upgrade to the latest version using the bun upgrade command. In short, Bun is a game-changer for JavaScript and TypeScript development - it's fast, efficient, and easy to use. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into NVIDIA-AI-Blueprints/video-search-and-summarization — fresh off the trending list. 🔗 https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization 📝 Suite of reference architectures for building GPU-accelerated vision agents and AI-powered video analytics applications. ────────────────────────────── The NVIDIA AI Blueprint for Video Search and Summarization (VSS) is a suite of reference architectures for building vision agents and AI-powered video analytics applications. It brings together accelerated vision microservices, vision language models (VLMs), and large language models (LLMs) to enable real-time video intelligence, downstream analytics, and agentic processing. Key features include real-time video intelligence, downstream analytics, and agentic and offline processing. The blueprint is designed for video analysts and IT engineers, as well as GenAI developers and machine learning engineers, providing a range of configuration options and customization possibilities. To get started, users can follow the Quickstart Guide for a launchable deployment or Docker Compose deployment, with system requirements including Ubuntu 22.04 or 24.04, NVIDIA Driver 580.105.08, and Docker 27.2.0+.

print("NVIDIA VSS blueprint streamlines video analytics and summarization with AI")

One-liner takeaway: The NVIDIA VSS blueprint revolutionizes video analytics by integrating AI-powered vision agents for smarter, more efficient processing and summarization. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet czlonkowski/n8n-mcp: a gem from today's GitHub trending list. 🔗 https://github.com/czlonkowski/n8n-mcp 📝 A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflows for you ────────────────────────────── n8n-MCP is a Model Context Protocol server that bridges the gap between n8n's workflow automation platform and AI models. It provides comprehensive access to n8n node documentation, properties, and operations, enabling AI assistants like Claude to understand and work with n8n nodes effectively. The server offers structured access to 1,650 n8n nodes, including core and community nodes, with detailed schemas and documentation. It also provides real-world examples and a template library to help users build efficient workflows. To get started, users can try the free tier on dashboard.n8n-mcp.com with 100 tool calls per day, or self-host the server using npx, Docker, or Railway. The project supports multiple AI-powered IDEs and tools, including Claude Code, Visual Studio Code, and Cursor. Key features include node discovery, configuration, and validation, as well as workflow building and deployment. The project also provides a comprehensive guide for setting up and using n8n-MCP with Claude Projects. The target audience includes developers, marketers, and analysts who want to automate their workflows efficiently using n8n and AI tools. Technical highlights include support for multiple programming languages, a large template library, and a robust validation system. In summary, n8n-MCP is a powerful tool that enables AI assistants to work seamlessly with n8n nodes, making it an essential resource for anyone looking to automate their workflows with ease: Automate your workflows with n8n-MCP and take your productivity to the next level! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 anthropics/skills just hit the trending charts — here's why it matters. 🔗 https://github.com/anthropics/skills 📝 Public repository for Agent Skills ────────────────────────────── The anthropics/skills GitHub repository is a treasure trove of skills for Claude, showcasing a wide range of tasks that can be accomplished using this technology. These skills are essentially folders containing instructions, scripts, and resources that Claude can load dynamically to improve performance on specialized tasks. The skills in this repository cover everything from creative applications like art and music to technical tasks like testing web apps and enterprise workflows. To get started, you can browse through the various skills in the repository, each of which is self-contained in its own folder with a SKILL.md file containing instructions and metadata. You can also use the template skill provided as a starting point to create your own custom skills. The repository is divided into several sections, including skills, spec, and template. The skills section contains a wide range of example skills, while the spec section outlines the Agent Skills specification. The template section provides a template for creating new skills. To try out the skills in the repository, you can register the repository as a Claude Code Plugin marketplace and install specific skills. You can also use the skills in Claude.ai or upload custom skills via the Claude API. One of the key technical highlights of the repository is the use of YAML frontmatter in the SKILL.md files to define the skill's metadata. This allows for easy creation and modification of skills. The repository is aimed at a wide range of audiences, including developers, designers, and enterprise users. Whether you're looking to create custom skills or simply want to learn more about the capabilities of Claude, this repository is a great resource. In short, the anthropics/skills repository is a powerful tool for unlocking the full potential of Claude - and with great skills comes great AI power! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet influxdata/telegraf: a gem from today's GitHub trending list. 🔗 https://github.com/influxdata/telegraf 📝 Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitrary data. ────────────────────────────── Telegraf is a powerful agent for collecting, processing, and writing metrics, logs, and other data. It offers a wide range of plugins (over 300) to cover various functionalities such as system monitoring, cloud services, and message passing. With TOML configuration, users can easily set up and customize Telegraf. It compiles into a standalone static binary, making deployment a breeze. Telegraf is designed for a wide range of users, from developers to system administrators, who need to collect and process data from various sources. Whether you're working with devices, logs, messaging, or system monitoring, Telegraf has got you covered. To get started, users can define a TOML configuration with their desired plugins and settings, and then pass it to Telegraf. The agent will collect data from inputs at each interval and send it to outputs at each flush interval. With a large community of over 1,200 contributors, Telegraf is constantly evolving and improving. The project has a comprehensive documentation, including tutorials, reference materials, and a contributing guide for those who want to get involved. In a nutshell, Telegraf is the go-to solution for data collection and processing - and with its flexibility and customizability, it's an essential tool for anyone working with data. So, what are you waiting for? Join the Telegraf community today and start collecting, processing, and writing your data with ease! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet ruvnet/RuView: a gem from today's GitHub trending list. 🔗 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. ────────────────────────────── RuView is a WiFi sensing platform that turns radio signals into spatial intelligence, allowing you to detect people, measure breathing and heart rate, track movement, and monitor rooms — through walls, in the dark, with no cameras or wearables. The system uses Channel State Information (CSI) from low-cost ESP32 sensors to capture disturbances in WiFi signals caused by human presence and movement. Key features include presence and occupancy detection, vital sign monitoring, activity recognition, environment mapping, and sleep quality monitoring. RuView runs on edge hardware, with no cloud or internet required, and uses spiking neural networks that adapt in under 30 seconds. The system is ideal for low-power edge applications, such as elderly care, hospital patient monitoring, and retail occupancy tracking. With RuView, you can turn ordinary WiFi into a spatial intelligence system — and that's a game-changer. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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⚡ supertone-inc/supertonic is making waves. Here's the full picture. 🔗 https://github.com/supertone-inc/supertonic 📝 Lightning-Fast, On-Device, Multilingual TTS — running natively via ONNX. ────────────────────────────── Supertonic is an on-device, lightning-fast text-to-speech system that runs entirely on your device, ensuring complete privacy and zero network dependency. Its key features include low-latency speech generation, compact ONNX assets, and accurate reading with fewer repeat and skip failures. To get started, simply install the Python SDK using pip install supertonic and generate speech with the provided examples. The repository includes ready-to-use examples across multiple ecosystems, such as Python, Node.js, browser, mobile, and native runtimes. From a technical perspective, Supertonic utilizes ONNX Runtime for cross-platform inference and supports batch processing for improved throughput. The system is designed to handle natural text inputs with complex prose, punctuation, abbreviations, and proper nouns. With support for 31 languages and various expression tags like <laugh>, <breath>, and <sigh>, Supertonic is an ideal choice for developers seeking a flexible and efficient text-to-speech solution. In a nutshell, Supertonic is the perfect tool for anyone looking to add high-quality, on-device text-to-speech capabilities to their application - it's fast, private, and accurate, making it a game-changer in the world of TTS technology. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 K-Dense-AI/scientific-agent-skills landed on trending. Worth a proper look. 🔗 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. ────────────────────────────── The Scientific Agent Skills repository on GitHub is a comprehensive collection of 135 ready-to-use scientific and research skills for any AI agent that supports the open Agent Skills standard. This repository, created by K-Dense, provides a wide range of skills across multiple scientific domains, including bioinformatics, cheminformatics, proteomics, and more. These skills enable your AI agent to seamlessly work with specialized scientific libraries, databases, and tools. The repository includes 100+ scientific databases, 70+ optimized Python package skills, and 9 scientific integration skills, among others. To get started, you can install the skills using npx or the GitHub CLI. The skills are well-documented, with examples, use cases, and best practices. This repository is maintained and supported by the K-Dense team, with regular updates and community contributions. In summary, the Scientific Agent Skills repository is a powerful tool for transforming your AI agent into a research assistant capable of executing complex multi-step scientific workflows. With the ability to access 100+ databases and utilize 70+ optimized Python packages, this repository is a game-changer for scientists and researchers: Transform your AI coding agent into an 'AI Scientist' and accelerate your research today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe