Github Top Repositories

🔍 Deep-diving into cathrynlavery/diagram-design — fresh off the trending list. 🔗 https://github.com/cathrynlavery/diagram-design 📝 29 editorial diagram types for Claude Code. Self-contained HTML + SVG. No shadows, no Mermaid-slop. ────────────────────────────── The Diagram Design GitHub repository is a game-changer for developers who want to create editorial-quality diagrams without the hassle of generic templates or tedious design tools. This repository offers 27 types of diagrams, from architecture sketches to flowcharts, and even provides a Claude Code skill that can read your website and match your brand's colors and fonts in just 60 seconds. The key features of this repository include: * Diagram types: 27 types of diagrams, including architecture, flowchart, sequence, and more * Brand matching: the skill can read your website and match your brand's colors and fonts * Customizable: you can override the default styles and customize the diagrams to fit your needs * Accessible: the diagrams are accessible by default, with features like WCAG AA contrast and semantic role names The repository is suitable for developers who want to create high-quality diagrams quickly and easily, without requiring extensive design experience. The code is well-organized, and the

README

file provides clear instructions on how to get started. In short, Diagram Design is a powerful tool that can help you create stunning diagrams in no time, and its flexibility and customizability make it a must-have for any developer. So why settle for generic diagrams when you can have editorial-quality diagrams that match your brand? ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet PrimeIntellect-ai/prime-agent: a gem from today's GitHub trending list. 🔗 https://github.com/PrimeIntellect-ai/prime-agent 📝 A self-improving RLM agent for coding workflows and long-running autonomous tasks. ────────────────────────────── Meet Prime Agent, an open-source coding and research agent designed for general and long-running work. It's built around two core abstractions: the Recursive Language Model (RLM) and the Continual Harness. The RLM treats context as variables and tools like recursive subagents as function calls, while the Continual Harness stores supplemental prompts, memories, and reusable subagent specifications as durable state. Key features include persistent Python control environment, daemon-backed agents, and direct agent-to-agent communication. To get started, install the latest stable release using

curl -fsSL https://app.primeintellect.ai/prime-agent/install.sh | sh

and run

prime-agent

in your project directory. Prime Agent is ideal for researchers, developers, and power users who need a robust tool for long-running work. With its autonomous mode, heartbeats and schedules, and persistent goals, you can focus on your work without interruptions. In a nutshell, Prime Agent is your ultimate sidekick for tackling complex tasks - it's like having a super-smart, self-improving assistant that's got your back! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 practical-tutorials/project-based-learning just hit the trending charts — here's why it matters. 🔗 https://github.com/practical-tutorials/project-based-learning 📝 Curated list of project-based tutorials ────────────────────────────── The practical-tutorials/project-based-learning GitHub repository is a treasure trove of hands-on learning experiences for aspiring software developers. The repo contains a vast collection of tutorials, each focusing on building a specific application from scratch, using various programming languages such as C#, C/C++, Clojure, Dart, and many more. These tutorials cover a wide range of topics, including network programming, OpenGL, and game development. To get started, simply fork the repository and refer to the CONTRIBUTING.md file for guidelines. Whether you're interested in building a Twitter bot with Clojure, a 2D Breakout game clone in C++ with OpenGL, or a Simple RPG Game in C#, this repository has something for everyone. The tutorials are designed to help developers of all levels gain practical experience and improve their coding skills. So, what are you waiting for? Dive into the world of project-based learning and take your coding skills to the next level - build something from scratch today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ calesthio/OpenMontage is making waves. Here's the full picture. 🔗 https://github.com/calesthio/OpenMontage 📝 World's first open-source, agentic video production system. 12 production pipelines, 100+ tools, 700+ agent skill and production-knowledge files. Turn your AI coding assistant into a full video production studio. ────────────────────────────── Introducing OpenMontage, the first open-source, agentic video production system. This innovative platform allows you to create stunning videos by simply describing what you want in plain language. Your AI coding assistant handles everything from research and scripting to asset generation, editing, and final composition. Key features include the ability to start from a reference video, analyze its transcript, pacing, scenes, and style, and generate a grounded production plan. You can also use the Backlot living storyboard to visualize your production's progress and approve assets before rendering. Technical highlights include support for various AI coding assistants, such as Claude Code, Cursor, and Copilot, as well as integration with providers like Bloome and Atlas Cloud. The system also includes a self-review process with multi-point validation and auditable decision logs. Usage is straightforward: simply clone the repository, install the prerequisites, and run the setup script. Then, open the project in your AI coding assistant and describe your desired video. Audience includes anyone interested in video production, from hobbyists to professionals. With OpenMontage, you can create high-quality videos without requiring extensive video editing experience. In summary, OpenMontage is a game-changer for video production, and with its open-source nature, it's an exciting project to watch and contribute to: Turn your AI coding assistant into a full video production studio and create stunning videos with ease! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: jaywcjlove/awesome-mac — let's break it down. 🔗 https://github.com/jaywcjlove/awesome-mac 📝  This project is dedicated to collecting high-quality macOS software and organizing them systematically by different categories for easy search and use. ────────────────────────────── The jaywcjlove/awesome-mac GitHub repository is a curated list of high-quality macOS software, organized by category for easy search and use. With a wide range of applications, from text editors and office tools to developer utilities and design software, this repository has become a comprehensive resource for macOS users. The project welcomes contributions and suggestions, with a contributing guidelines in place to ensure the list remains refined and up-to-date. Whether you're a developer, designer, or simply a macOS user, this repository has something for everyone. Star and fork the project to support it, and discover new macOS software to enhance your workflow. The takeaway: awesome-mac is your one-stop-shop for all things macOS, making it easy to find the perfect tools to boost your productivity! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into harveyai/harvey-labs — fresh off the trending list. 🔗 https://github.com/harveyai/harvey-labs 📝 A benchmark built to evaluate and improve agent capabilities for supporting legal work. ────────────────────────────── The Harvey LAB is an open-source benchmark for evaluating agents on real legal work. It consists of a dataset of tasks and an execution harness for running and evaluating agents. The key features of Harvey LAB include 1671 tasks across 24+ legal practice areas, with a test suite to validate the task schema. To get started, users can follow the full walkthrough in the tutorial.md guide. The project is designed for researchers and developers interested in evaluating the performance of large language models (LLMs) in legal work. The architecture, evaluation methodology, and contributing guidelines are well-documented, making it easy for users to understand and contribute to the project. The takeaway: Harvey LAB is revolutionizing the way we evaluate AI agents in legal work, and you can be a part of it! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 huggingface/transformers is trending — and it deserves your attention. 🔗 https://github.com/huggingface/transformers 📝 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. ────────────────────────────── The huggingface/transformers GitHub repository provides a comprehensive library for state-of-the-art machine learning models, supporting text, computer vision, audio, video, and multimodal tasks. At its core, Transformers serves as a model-definition framework, allowing for seamless compatibility across various training frameworks, inference engines, and modeling libraries. The library offers over 1 million model checkpoints on the Hugging Face Hub, making it easy to find and use pre-trained models for specific tasks. With a simple and customizable API, users can quickly get started with tasks like text generation, chat, automatic speech recognition, image classification, and visual question answering. Key features of the library include: * Easy-to-use state-of-the-art models with high performance and low barrier to entry * Lower compute costs and smaller carbon footprint through shared trained models and reduced compute time * Flexibility to choose the right framework for training, evaluation, and production * Customizable models and examples for specific use cases The library is suitable for researchers, engineers, and developers, providing a unified API for using pre-trained models and a few user-facing abstractions to learn. To get started, users can install the library using pip or uv and explore the Hugging Face Hub for pre-trained models. The library also provides a Pipeline API for high-level inference and a range of examples for different tasks and modalities. In summary, the huggingface/transformers library is a powerful tool for machine learning tasks, offering a wide range of pre-trained models, a simple API, and flexibility to choose the right framework. Whether you're a researcher, engineer, or developer, this library can help you achieve state-of-the-art results with ease. Transform your machine learning workflow with huggingface/transformers - the ultimate library for state-of-the-art models! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet paperclipai/paperclip: a gem from today's GitHub trending list. 🔗 https://github.com/paperclipai/paperclip 📝 The open-source app everyone uses to manage agents at work ────────────────────────────── Paperclip is an open-source platform that helps you manage AI agents for work. It's like a task manager, but under the hood, it's a powerful tool that lets you define goals, assign tasks, and track progress. You can bring your own agents, assign them roles, and track their work and costs from one dashboard. Key features include a Node.js server, React UI, and support for multiple agents like OpenClaw, Codex, and Claude. It also has features like goal alignment, cost control, and governance. The platform is built around four pillars: Agentic Task Manager, Org Chart for Agents, Agent Employee Training, and Agentic OS. those who want to build autonomous AI companies, coordinate multiple agents, and manage their work from one place. It's also great for those who want to monitor costs, enforce budgets, and have a process for managing agents that feels like using a task manager. Paperclip is special because it handles the hard orchestration details correctly, with features like atomic execution, persistent agent state, and governance with rollback. In short, Paperclip is the ultimate tool for managing AI agents for work, and with it, you can manage business goals, not pull requests. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 stablyai/orca just hit the trending charts — here's why it matters. 🔗 https://github.com/stablyai/orca 📝 Orca is the ADE for working with a fleet of parallel agents. Run any coding agent with your own subscription. Available on desktop, mobile and VPS. ────────────────────────────── Meet Orca, the AI orchestrator designed for 100x builders. It allows you to run multiple agents like Codex, ClaudeCode, and OpenCode in parallel worktrees, all tracked in one place. Key features include a mobile companion app, parallel worktrees, terminal splits, design mode, and native GitHub and Linear integration. You can use Orca with any CLI agent, and it supports a wide range of agents, including Claude Code, Codex, and OpenCode. With Orca, you can streamline your workflow, increase productivity, and focus on building. Orca is perfect for developers, builders, and anyone looking to unlock their full potential. In short, Orca is the ultimate tool for builders who want to build faster and smarter - it's like having a superpower in your workflow. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into HKUDS/DeepTutor — fresh off the trending list. 🔗 https://github.com/HKUDS/DeepTutor 📝 DeepTutor: Lifelong Personalized Tutoring.https://deeptutor.info/. ────────────────────────────── Introducing DeepTutor, a lifelong personalized tutoring platform that aims to revolutionize the way we learn. With a wide range of features, DeepTutor provides a comprehensive learning experience, including Guided Learning, Knowledge Center, and Chat functionality. The platform is built using Python 3.11+ and Next.js 16, and is designed to be highly customizable and extensible. Key features include support for multiple LLM providers, Document Parsing engines, and retrieval roles for queries. Technical highlights include a LightRAG Server retrieval engine, a PyMuPDF4LLM parsing engine, and a FAISS vector backend for large knowledge-base retrieval. Audience includes anyone looking for a personalized learning experience, from students to professionals. Get started with DeepTutor today and discover a new way to learn! One-liner takeaway: DeepTutor is your personalized learning companion, empowering you to reach new heights with AI-driven insights and guidance. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet 3b1b/manim: a gem from today's GitHub trending list. 🔗 https://github.com/3b1b/manim 📝 Animation engine for explanatory math videos ────────────────────────────── Manim is a powerful animation engine designed for creating explanatory math videos. It allows for precise programmatic control over animations, making it perfect for educational content. The project has two versions: the original 3b1b/manim repository and the community-driven ManimCommunity/manim fork. To get started with Manim, you can install it via pip using pip install manimgl. The engine requires FFmpeg, OpenGL, and optionally LaTeX for rendering mathematical equations. You can also install it on Linux, Windows, or Mac OSX by following the provided instructions. Manim offers a range of features, including: - Customizable animations and scenes - Support for various input formats, such as Python scripts and LaTeX equations - Options for rendering animations as videos or images The project has an active community, with documentation available at 3b1b.github.io/manim and a Chinese version at docs.manim.org.cn. Contributions are welcome, and the project is licensed under the MIT license. In short, Manim is a game-changer for creating engaging, math-focused animations - and the best part? It's free and open-source, empowering creators to bring complex concepts to life with ease! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 anthropics/skills is trending — and it deserves your attention. 🔗 https://github.com/anthropics/skills 📝 Public repository for Agent Skills ────────────────────────────── The anthropics/skills repository on GitHub is a treasure trove of skills for Claude, designed to enhance its performance on specialized tasks. These skills are essentially folders containing instructions, scripts, and resources that Claude can load dynamically. The repository includes a wide range of skills, from creative applications like art and music to technical tasks like testing web apps and enterprise workflows. To get started with these skills, you can browse through the repository and explore the different folders, each containing a SKILL.md file with instructions and metadata. You can also use the template-skill as a starting point to create your own custom skills. The repository provides a spec folder with the Agent Skills specification and a template folder for skill templates. The skills in this repository are easy to use and can be installed through Claude Code, Claude.ai, or the Claude API. For example, you can register the repository as a Claude Code Plugin marketplace and install specific skills like document-skills or example-skills. You can then use these skills by mentioning them in your commands, such as "Use the PDF skill to extract the form fields from path/to/some-file.pdf". The anthropics/skills repository is a valuable resource for developers, partners, and anyone looking to improve Claude's capabilities. With its open-source and source-available skills, it's an excellent starting point for creating custom skills and exploring the possibilities of Agent Skills. So, why not dive in and start creating your own skills today - the possibilities are endless with Claude and the anthropics/skills repository! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 vitali87/code-graph-rag caught my eye on GitHub Trending today. 🔗 https://github.com/vitali87/code-graph-rag 📝 The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs ────────────────────────────── Code-Graph-RAG is a powerful tool that parses a multi-language codebase, builds a knowledge graph, and allows you to query, edit, and optimize the code in plain English. Key features include support for multiple languages, structural search and replace, data-flow tracing, and optimization against language best practices. Usage is straightforward: point Code-Graph-RAG at a repository, and it extracts functions, classes, methods, and relationships, storing them as an interconnected graph. You can then ask questions about the codebase, retrieve source code, edit code through the agent, and optimize it. From a technical perspective, Code-Graph-RAG uses Tree-sitter for parsing and Memgraph for the knowledge graph. The system has two components: a multi-language parser and an interactive CLI that turns natural language into Cypher queries. This tool is designed for developers and organizations looking to streamline their code management and optimization processes. With Code-Graph-RAG, you can query and edit your codebase directly, making it an essential tool for any development team. In short, Code-Graph-RAG is a game-changer for code management - it's like having a superpower for your codebase. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe