Github Top Repositories

🔍 Deep-diving into holaboss-ai/holaOS — fresh off the trending list. 🔗 https://github.com/holaboss-ai/holaOS 📝 Open-source All in One AI agent workspace. Run any agent — Claude Code, Codex — across your tools (100+ integrations + MCP), apps, browser, and files, with shared memory. Built-in models or BYOK. ────────────────────────────── Meet holaOS, the ultimate workspace for you and your agent. It allows you to run any agent, including Claude Code, Codex, or the built-in holaOS agent, in one local-first workspace. This means you can work with multiple agents, sharing the same memory, tools, and skills, without having to switch between them. Key features include: - Running any agent in one workspace - Shared memory across agents and sessions - Support for frontier models, including Kimi K3, GLM 5.2, GPT 5.6, Claude Opus 5, and Fable 5 - Ability to bring your own model keys - HolaApps, which allow you to install apps from the in-workspace marketplace and use them side-by-side with your agent - Skills, integrations, and Model Context Protocol (MCP) support Usage is straightforward: simply download and install the desktop app, and you're ready to go. The app is open-source and free to start, with optional enterprise features available. From a technical standpoint, holaOS is built using TypeScript and Electron, and supports macOS, Windows, and Linux platforms. The target audience for holaOS includes anyone looking for a flexible and powerful workspace for their agent, including developers, researchers, and business users. In summary, holaOS is a game-changer for anyone working with agents, offering a flexible, powerful, and easy-to-use workspace that can be customized to meet your needs. Get started with holaOS today and experience the power of a unified workspace for you and your agent! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ NVIDIA-NeMo/Switchyard is making waves. Here's the full picture. 🔗 https://github.com/NVIDIA-NeMo/Switchyard 📝 No description. ────────────────────────────── Introducing Switchyard, a Rust proxy and library designed for Large Language Model (LLM) traffic management. It routes requests across multiple providers, translates between OpenAI and Anthropic APIs, records operational metrics, and provides typed, composable routing algorithms. Main features include protocol translation, multi-backend routing, and operational metrics. You can use Switchyard as a launcher, server, or library, making it a versatile tool for managing LLM traffic. To get started, you can choose the launcher path to run coding agents like Claude Code or Codex through Switchyard, the server path to run Switchyard as a standalone proxy, or the library path to embed routing algorithms in your own Rust application. Technical highlights include support for various routing strategies, such as LLM classifier, stage router, escalation router, and random routing. Switchyard also provides a simple architecture for routing and translation. Switchyard is designed for developers and researchers working with LLMs, especially those who need to manage traffic across multiple models and providers. In a nutshell, Switchyard is your one-stop solution for LLM traffic management - route, translate, and optimize your way to AI efficiency. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 smicallef/spiderfoot is trending — and it deserves your attention. 🔗 https://github.com/smicallef/spiderfoot 📝 SpiderFoot automates OSINT for threat intelligence and mapping your attack surface. ────────────────────────────── SpiderFoot is an open-source intelligence (OSINT) automation tool that integrates with numerous data sources and utilizes various methods for data analysis. It offers a web-based interface and command-line functionality, all written in Python 3 and MIT-licensed. Key features include over 200 modules, a YAML-configurable correlation engine, and support for CSV/JSON/GEXF export. It also has TOR integration for dark web searches and a Dockerfile for Docker-based deployments. This tool can be used for both offensive and defensive purposes, such as reconnaissance or gathering information about exposed internet assets. It's highly configurable, fully documented, and has a visual interface. The target audience includes security professionals, developers, and anyone interested in OSINT and data analysis. Overall, SpiderFoot is a powerful tool for automating OSINT tasks and analyzing large amounts of data. With its extensive features and customization options, it's an essential tool for anyone looking to streamline their OSINT workflow: SpiderFoot is your ultimate OSINT sidekick! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: megadose/holehe — let's break it down. 🔗 https://github.com/megadose/holehe 📝 holehe allows you to check if the mail is used on different sites like twitter, instagram and will retrieve information on sites with the forgotten password function. ────────────────────────────── Holehe is an Open-Source Intelligence (OSINT) tool that efficiently finds registered accounts from emails. It checks if an email is attached to an account on over 120 sites like Twitter, Instagram, and Imgur. Key features include: - retrieving information using the forgotten password function - not alerting the target email - running on Python 3 To use Holehe, you can install it via pip3 install holehe, git clone, or docker. holehe test@gmail.com is a simple command to run the tool. For more complex usage, you can integrate it into your Python applications. The output is a dictionary with information like rate limits, account existence, and sometimes partially obfuscated recovery emails and phone numbers. This tool is perfect for security researchers, OSINT investigators, and anyone interested in email reconnaissance. One-liner takeaway: Holehe is a must-have OSINT tool that helps you uncover hidden email accounts without alerting the target. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ macro-inc/macro is making waves. Here's the full picture. 🔗 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. ────────────────────────────── Hey there, let's check out the Macro GitHub repo. Macro is an all-in-one workspace that combines email, messages, docs, tasks, agents, and CRM into a single, fast interface with shared team-level memory. It's designed to be a single operating system for your team, eliminating the need for multiple tools. The key features of Macro include: - Modular blocks that work together like Lego, allowing for customization and extensibility - Bidirectional graph for cross-references between different surfaces, such as docs and tasks - Real-time collaborative editing with CRDTs, making it feel like you're editing on the same computer In terms of technical highlights, Macro is built with SolidJS and Rust for speed and reliability. The CRDT collaboration system allows for seamless editing and conflict resolution, even with multiple agents operating simultaneously. Macro is suitable for small companies or teams within larger companies, looking for an all-in-one workspace solution. The ideal audience includes teams seeking to streamline their workflow, reduce tool clutter, and improve collaboration. One-liner takeaway: Simplify your team's workflow with Macro, the all-in-one workspace that's about to revolutionize how you get things done! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into unslothai/unsloth — fresh off the trending list. 🔗 https://github.com/unslothai/unsloth 📝 Local UI to run and train LLMs and diffusion models, including Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, FLUX and more. ────────────────────────────── Unsloth is a cutting-edge desktop app that allows users to run and train AI models locally, with support for various types of models. It features a user-friendly interface, native support for CPU, NVIDIA, AMD, and Intel hardware, and multi-GPU setups. Users can download the app for Windows, macOS, or Linux, and start using it right away. The app offers a range of features, including model training, fine-tuning, and deployment, as well as private and unlimited web search, deep research, and RAG. It also supports image and video diffusion, audio models, and reinforcement learning. Unsloth is designed for developers, researchers, and AI enthusiasts who want to work with AI models locally, without relying on cloud services. The app is free to use and offers a range of community resources, including documentation, tutorials, and forums. To get started with Unsloth, users can simply download the app and follow the installation instructions. The app also offers a web-based interface and a command-line interface for more advanced users. One of the key benefits of Unsloth is its ability to run AI models locally, which provides a high level of security and control for users. The app also offers remote access capabilities, allowing users to access their models from anywhere. Overall, Unsloth is a powerful and flexible tool for working with AI models locally, and it offers a range of features and benefits that make it an attractive choice for developers, researchers, and AI enthusiasts. Takeaway: Unsloth is the ultimate tool for running and training AI models locally, offering a unique combination of power, flexibility, and security. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 altic-dev/FluidVoice is trending — and it deserves your attention. 🔗 https://github.com/altic-dev/FluidVoice 📝 Fastest and only macOS Dictation app with on-device STT and custom trained AI enhancement model. A local Wispr Flow alternative. ⭐ helps a ton :) Windows & iOS waitlist open. Linux soon. ────────────────────────────── FluidVoice is an open-source, on-device AI-enhanced voice-to-text dictation app for macOS. It features Fluid Intelligence, a local AI model for smart formatting and context-aware capitalization, and supports various speech models like Nemotron, Parakeet, and Whisper. To get started, brew install --cask fluidvoice or download the latest release. Grant microphone and accessibility permissions, set your hotkey, and go through onboarding to choose your voice model. Key Features: - On-device AI enhancement with Fluid Intelligence - Multiple speech models for different languages and latency needs - Command Mode for voice control and Write Mode for dictation in any text field - Live preview with notch support and adaptive theming Technical Highlights: - Built with Swift and Swift Package Manager - Supports Apple Silicon and Intel Macs (via Whisper models) - Requires macOS 15.0 or later and ~1 GB disk space for a voice model Audience: - Individuals looking for a free, open-source dictation app with on-device AI enhancement - Developers interested in contributing to the project or building from source Get started with FluidVoice today and experience fast, accurate, and private dictation on your Mac - your voice, your words, your way. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 cactus-compute/needle is trending — and it deserves your attention. 🔗 https://github.com/cactus-compute/needle 📝 14MB foundation model for tiny devices; phones, wearables, smart home, and robots. ────────────────────────────── The Needle repository on GitHub is home to an open 45M-parameter model designed for tool calling, device use, and structured extraction. This model is unique in that it's a single 14MB binary that requires approximately 28MB of RAM to run a full session. Key features of the Needle model include its self-contained nature, with weights baked into the engine, a simple contract for tool calls, confidence-gated responses, and bounded memory usage. To use the Needle model, you can install it via pip with pip install cactus-needle and then describe your tools to interact with the model. The model supports tool retrieval, where it can select the most relevant tools based on the input query, and confidence-gated responses, where the model returns a confidence score with each response. Technical highlights of the Needle model include its use of a Simple Attention Network architecture, which is a dense small-model recipe that incorporates a Hadamard MLP, GQA attention, and engram key-value memory. The model is also compressed using CQ2-bit with Cactus Quants, which reduces its size while maintaining its performance. The Needle model is suitable for a wide range of audiences, including developers, researchers, and anyone interested in natural language processing and tool calling. With its unique combination of features and technical advancements, the Needle model is a valuable resource for anyone looking to explore the possibilities of AI-powered tool calling and extraction. In summary, the Needle model is a powerful and efficient tool for natural language processing and tool calling, with a unique combination of features and technical advancements that make it an exciting and valuable resource - and with Needle, you can have the power of a large language model in the palm of your hand. ────────────────────────────── 🧠 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 GitHub repository is a treasure trove of skills for Claude, a platform that leverages these skills to improve performance on specialized tasks. These skills are essentially folders containing instructions, scripts, and resources that Claude loads dynamically. The repository includes a wide range of skills, from creative applications like art and music to technical tasks such as testing web apps and enterprise workflows. To get started, you can browse through the various skills in the repository, which are all self-contained in their own folders with a SKILL.md file. Many of these skills are open source, while others, like the document creation and editing skills, are source-available. You can use these skills as inspiration for your own or to understand different patterns and approaches. The repository also includes a template-skill that you can use as a starting point to create your own custom skills. Creating a basic skill is straightforward, requiring only a folder with a SKILL.md file containing YAML frontmatter and instructions. The skills can be used in various ways, including through Claude Code, Claude.ai, and the Claude API. Whether you're a developer looking to teach Claude how to use specific software or an enterprise seeking to improve workflows, the anthropics/skills repository has something to offer. One-liner takeaway: With the anthropics/skills repository, you can unlock Claude's full potential and teach it new tricks to streamline your workflow and boost productivity! ────────────────────────────── 🧠 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 an open-source, graph-native infrastructure for building context and accountable AI systems. It's designed to ingest enterprise data, extract relevant information, and construct a knowledge graph with full decision provenance. Key features include graph analytics, deterministic reasoning, ontology management, and end-to-end traceability. Technical highlights of Semantica include polyglot graph storage, RDF and LPG support, and compliance with W3C standards. The platform is self-hostable, auditable, and governed, with zero vendor lock-in. Audience for Semantica includes AI/ML platform teams, data platform teams, compliance and risk teams, and regulated enterprises. It's ideal for high-stakes, regulated domains where explainable and trustworthy AI decision-making is crucial. To get started with Semantica, simply run pip install semantica and explore the ContextGraph API. With Semantica, you can build a transparent and accountable AI system that provides real, structured answers to "why did this happen?" In short, Semantica is the missing infrastructure layer that brings trust and transparency to your AI decisions. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 cathrynlavery/diagram-design just hit the trending charts — here's why it matters. 🔗 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 provides a Claude Code skill for creating high-quality, editorial diagrams that match your brand. With 27 visual types and three static variants, you can easily generate diagrams such as architecture sketches, flowcharts, and pyramids. The skill uses a shared-memory hub and semantic patterns to describe behavior separately from layout, allowing for flexible and accessible diagrams. To get started, you can install the skill using /plugin marketplace add cathrynlavery/diagram-design for Claude Code or codex plugin marketplace add cathrynlavery/diagram-design for Codex. The skill will then pull your brand's colors and typography from your website and apply them to the diagrams. The repository also includes an online gallery where you can browse the available diagrams. Overall, the diagram-design skill is a powerful tool for creating high-quality, accessible diagrams that match your brand's style. Take your diagrams to the next level with this skill - no more generic rounded boxes! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 21-Day CCNA & CCNP Sprint – Aug 17 to Sep 6 🤝 Peer Group – Share Insights | Exchange Knowledge | Support Each Other No more studying alone. Join a community of CCNA/CCNP candidates, learn together, and win prizes. How it works: ① DM admin: "I'M IN + cert name" ② Join the group ③ Check in 18/21 days → win 🎁 Prizes (first come, first served): $50 Amazon card ×1 | SD-Access Training ×1 | SD-WAN Training ×1 | CCNA Pro Package ×10 | Free Learning Pack (all finishers) Daily check-in: 1️⃣ What you learned 2️⃣ Explain it in your own words 3️⃣ (Optional) Ask the group Join now: https://chat.whatsapp.com/KZrAj2HZ3Y5K9UhhNhrApf DM to register: https://wa.me/8619559123054

⚡ cactus-compute/needle is making waves. Here's the full picture. 🔗 https://github.com/cactus-compute/needle 📝 14MB foundation model for tiny devices; phones, wearables, smart home, and robots. ────────────────────────────── Needle 2 is a compact, open-source model for tool calling, device use, and structured extraction. It's a single 14MB binary that runs in approximately 28MB of RAM. Key features include a self-contained engine, simple contract for tool calls, and confidence-gated responses. Needle 2 is built on the Simple Attention Network architecture, which includes a Hadamard MLP, GQA attention, and engram key-value memory. The model is compressed to CQ2-bit with Cactus Quants and can be used for a variety of tasks, including tool calling, data extraction, and more. To use Needle 2, you can install the cactus-needle Python package and describe your tools using a simple contract. The model can then be used to call tools, extract structured data, and more. Audience: This model is suitable for developers and researchers looking for a compact, efficient, and easy-to-use model for tool calling and data extraction tasks. One-liner takeaway: Needle 2 is a powerful, compact model that makes it easy to build tool calling and data extraction applications with confidence-gated responses. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe