Github Top Repositories

⚡ stablyai/orca is making waves. Here's the full picture. 🔗 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. ────────────────────────────── Orca is the AI orchestrator for 100x builders, allowing you to run multiple agents like Codex, ClaudeCode, and Pi in parallel worktrees, tracked in one place. Key features include a mobile companion app, parallel worktrees, terminal splits, design mode, and native GitHub and Linear integration. orca also offers a CLI for scripting workflows and supports various agents. Usage is straightforward, with a user-friendly interface and extensive documentation. Technical highlights include WebGL rendering, infinite terminal splits, and auto-reconnect for remote worktrees. Orca is suitable for developers and power users looking to streamline their workflow. With Orca, you can script every workflow and stay productive on-the-go. Orca is the ultimate tool for AI-driven development - build faster, build smarter. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into semantica-agi/semantica — fresh off the trending list. 🔗 https://github.com/semantica-agi/semantica 📝 Graph-Native Infrastructure for Context and Accountable AI Systems ────────────────────────────── Semantica is a graph-native infrastructure for context and accountable AI systems, offering a comprehensive platform for decision intelligence, context management, and knowledge modeling. It provides a structured, queryable graph of everything an agent knows, decides, and reasons about, along with decision intelligence that makes every decision a first-class object, traceable, searchable by precedent, and causally linked. Key features include: - Context Graphs: a structured, queryable graph of everything an agent knows, decides, and reasons about - Decision Intelligence: every decision is a first-class object, traceable, searchable by precedent, and causally linked - AI Governance & Ontology: SHACL constraints, conflict detection, compliance rules, OWL generation, and SKOS vocabulary management - Full Auditability: W3C PROV-O provenance on every fact, with audit trails exportable to JSON, CSV, or RDF Semantica is designed for AI/ML platform teams, data platform teams, compliance, risk, and audit teams, regulated enterprises, platform and infra engineers, and data and knowledge engineers. It provides a polyglot graph storage with native support for RDF and Labeled Property Graphs, as well as drop-in integrations with popular tools and platforms. To get started, simply run

pip install semantica

and explore the platform's features and capabilities. With Semantica, you can build a knowledge graph from messy, multi-source data, and gain full decision provenance and explainable reasoning for your AI agents. In short, Semantica is the missing link between AI decisions and real-world accountability. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into macro-inc/macro — fresh off the trending list. 🔗 https://github.com/macro-inc/macro 📝 Macro is a unified workspace for teams: email, chat, docs, tasks, agents, calls, and CRM — @-linked together with shared AI memory. ────────────────────────────── Let's break down the Macro workspace. Macro is an all-in-one platform designed to unify email, messages, docs, tasks, and CRM into a single, fast interface with shared team-level memory. The platform is built around the concept of blocks, which are modular, extensible, and work together like Legos. Some of the key features of Macro include: - Multi-account email inbox with unified search and AI tools - Team chat designed for focused technical discussions - Task management built around chat, with bidirectional links to messages and emails - Docs with live collaboration, version control, and offline editing - CRM that keeps itself up to date, with bidirectional links to messages and emails The platform is built using SolidJS and Rust for speed and reliability. Macro is designed for small companies or teams within larger companies, and is dogfooded by the Macro team themselves. The platform's technical highlights include its use of a bidirectional graph to store cross-references between different blocks, and its CRDT-based collaboration system for live document editing. Overall, Macro is designed to be a single, unified platform for teams to work together, with all the tools and features they need to collaborate and get work done. With its focus on speed, reliability, and ease of use, Macro is an attractive option for teams looking to streamline their workflow. One-liner takeaway: Macro is the ultimate all-in-one workspace that unifies your team's tools and streamlines your workflow! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🔍 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