🔥 yt-dlp/yt-dlp is trending — and it deserves your attention.

🔗 https://github.com/yt-dlp/yt-dlp
📝 A feature-rich command-line audio/video downloader
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yt-dlp is a feature-rich command-line audio/video downloader that supports thousands of sites. It's a fork of youtube-dl, with a wide range of options for customizing downloads, including video selection, format selection, and post-processing. The tool can be installed using pip or by downloading pre-compiled binaries for various platforms.

The configuration file allows for further customization, and the tool also supports plugins and embedding in other applications. The project is actively maintained, with regular updates and a strong focus on community involvement.

Whether you're a casual user or a power user, yt-dlp has the features and flexibility you need to download your favorite videos and audio files.

So why settle for limited video downloaders when you can have it all with yt-dlp? Download it now and experience the power of unlimited video downloading!

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🧠 Channel: https://t.me/GithubRe

🚀 Meet karpathy/nn-zero-to-hero: a gem from today's GitHub trending list.

🔗 https://github.com/karpathy/nn-zero-to-hero
📝 Neural Networks: Zero to Hero
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The Neural Networks: Zero to Hero course is a comprehensive series of YouTube videos and Jupyter notebooks that take you on a journey from the basics of neural networks to building complex models like GPT. The course is designed for those with a basic knowledge of Python and a vague recollection of calculus from high school.

Key features of the course include building micrograd, a minimal neural network framework, and makemore, a character-level language model. You'll learn about backpropagation, training neural networks, and the overall framework of language modeling.

To get started, you can access the YouTube video lectures and Jupyter notebook files in the lectures/ directory. The course is suitable for anyone interested in learning about neural networks, from beginners to experienced practitioners.

Some technical highlights of the course include implementing a multilayer perceptron (MLP) character-level language model, introducing torch.Tensor and its subtleties, and building a Generatively Pretrained Transformer (GPT) from scratch.

The course is ideal for students, researchers, and practitioners who want to gain a deep understanding of neural networks and their applications.

In summary, this course is a hands-on guide to learning neural networks, and by the end of it, you'll be well on your way to becoming a neural network expert - so, join the journey and become a neural network hero!

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🧠 Channel: https://t.me/GithubRe

AI is moving fast. Accountability is not.

That is why we built the open source core of Forkit Dev.

Forkit Dev introduces Model Passports and Agent Passports so AI systems can be tracked, verified, and understood across their lifecycle.

Open source repo:
https://github.com/arpitasarker01/Forkit_Dev

If you care about trustworthy AI, open source infrastructure, model lineage, or compliance ready deployment, check it out and share your thoughts.

🎯 Lum1104/Understand-Anything landed on trending. Worth a proper look.

🔗 https://github.com/Lum1104/Understand-Anything
📝 Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
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Understand Anything is a revolutionary tool that turns any codebase, knowledge base, or docs into an interactive knowledge graph. This graph can be explored, searched, and questioned, making it easier to understand complex systems. The tool is compatible with various platforms, including Claude Code, Codex, Cursor, Copilot, and Gemini CLI.

The key features of Understand Anything include:
- Interactive knowledge graph: Every file, function, and class is a node that can be clicked, searched, and explored.
- Guided tours: Auto-generated walkthroughs of the architecture, ordered by dependency.
- Fuzzy and semantic search: Find anything by name or by meaning.
- Diff impact analysis: See which parts of the system your changes affect before you commit.

To get started, simply install the plugin using /plugin marketplace add Lum1104/Understand-Anything and /plugin install understand-anything. Then, analyze your codebase with /understand and explore the interactive dashboard with /understand-dashboard.

The tool is designed for anyone who wants to understand complex codebases, including developers, PMs, and power users. With its persona-adaptive UI, the dashboard adjusts its detail level based on who you are.

In short, Understand Anything is a game-changer for anyone who wants to unlock the secrets of complex codebases and knowledge bases. Stop reading code blind, start seeing the big picture — and discover the power of interactive knowledge graphs with Understand Anything.
You can now see the forest for the trees.

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🧠 Channel: https://t.me/GithubRe

💡 anthropics/claude-plugins-official just hit the trending charts — here's why it matters.

🔗 https://github.com/anthropics/claude-plugins-official
📝 Official, Anthropic-managed directory of high quality Claude Code Plugins.
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The anthropics/claude-plugins-official GitHub repository is a curated directory of high-quality plugins for Claude Code. It contains both internal plugins developed by Anthropic and third-party plugins from partners and the community.

To use these plugins, you can install them directly from the marketplace via /plugin install {plugin-name}@claude-plugins-official or browse for them in /plugin > Discover.

From a technical standpoint, each plugin follows a standard structure, including a plugin.json file with metadata and optional configurations for MCP servers, slash commands, agents, and skills.

This repository is ideal for Claude Code users, developers, and partners looking to extend the platform's functionality.

One-liner takeaway: Unlock Claude Code's full potential with the anthropics/claude-plugins-official repository, your one-stop shop for high-quality, community-driven plugins.

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🧠 Channel: https://t.me/GithubRe

🔥 colbymchenry/codegraph is trending — and it deserves your attention.

🔗 https://github.com/colbymchenry/codegraph
📝 Pre-indexed code knowledge graph for Claude Code, Codex, Cursor, OpenCode, and Hermes Agent — fewer tokens, fewer tool calls, 100% local
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CodeGraph is a tool that supercharges your coding experience with semantic code intelligence. It integrates with agents like Claude Code, Cursor, Codex CLI, opencode, and Hermes Agent to provide features like smart context building, full-text search, and impact analysis.

To get started, simply run the installer with npx @colbymchenry/codegraph or use a package manager like npm. The installer will guide you through the configuration process, including setting up your agent and initializing your project with codegraph init -i.

Key Features include:

* Framework-aware routes for web frameworks like Django, Flask, and Express
* Support for 19+ languages, including TypeScript, JavaScript, and Python
* 100% local operation, with no data leaving your machine

The Benchmark Results show that CodeGraph can reduce costs by 35%, tokens by 59%, and tool calls by 70%. Overall, CodeGraph is designed to help developers work more efficiently and effectively.

Supercharge your coding experience with CodeGraph - it's like having a personal coding assistant!

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🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into rohitg00/ai-engineering-from-scratch — fresh off the trending list.

🔗 https://github.com/rohitg00/ai-engineering-from-scratch
📝 Learn it. Build it. Ship it for others.
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The AI Engineering from Scratch curriculum is a comprehensive, 20-phase journey that equips students with the skills to build AI systems from the ground up. With 435 lessons, ~320 hours of content, and support for Python, TypeScript, Rust, and Julia, this curriculum aims to bridge the gap between AI theory and practical application. Each lesson follows a consistent structure, starting with the math behind an algorithm, then implementing it from scratch, and finally using it in a real-world context. The curriculum is designed to be free, open-source, and MIT-licensed. The target audience includes anyone who wants to understand how AI actually works, not just call APIs - you don't just learn AI, you build it, end-to-end, by hand. With a focus on hands-on learning and reusable artifacts, this curriculum is perfect for those who want to gain a deep understanding of AI engineering. In short, AI Engineering from Scratch is the ultimate resource for anyone looking to master the art of building AI systems from scratch - build it, don't just memorize it.

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🧠 Channel: https://t.me/GithubRe

🔥 Fincept-Corporation/FinceptTerminal is trending — and it deserves your attention.

🔗 https://github.com/Fincept-Corporation/FinceptTerminal
📝 FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
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The Fincept Terminal is a state-of-the-art financial intelligence platform that offers institutional-grade financial analytics, AI automation, and unlimited data connectivity. Its key features include multi-asset analytics, AI agents, and 100+ data connectors. To use the Fincept Terminal, you can either download the installer from the GitHub releases page or build it from source using CMake and Qt 6.8.3.

The platform is built using C++20 and Qt6 for the UI, and it also includes embedded Python for analytics. The

setup.sh

script can be used to install all dependencies and build the app automatically.

The Fincept Terminal is suitable for various audiences, including financial analysts, traders, and developers who want to leverage its real-time trading and quantitative analysis capabilities.

In short, the Fincept Terminal is a powerful tool that can help you make data-driven decisions in the financial sector, and its customizable workflows and AI quant lab make it an ideal choice for those who want to stay ahead of the curve.

Takeaway: The Fincept Terminal is the ultimate financial intelligence platform that can help you unlock new insights and opportunities in the financial sector.

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🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into multica-ai/andrej-karpathy-skills — fresh off the trending list.

🔗 https://github.com/multica-ai/andrej-karpathy-skills
📝 A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.
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The multica-ai/andrej-karpathy-skills GitHub repository offers a set of guidelines to improve the behavior of Claude Code, a coding assistant, by addressing common pitfalls observed by Andrej Karpathy. These guidelines are centered around four key principles: Think Before Coding, Simplicity First, Surgical Changes, and Goal-Driven Execution.

The CLAUDE.md file contains these principles, which can be installed as a Claude Code plugin or added to a project manually. The guidelines promote explicit reasoning, simplicity, and minimal changes, and they encourage the definition of success criteria to transform imperative tasks into verifiable goals.

These guidelines are suitable for developers and teams looking to improve the efficiency and reliability of their coding workflows. By following these principles, users can reduce unnecessary changes, overcomplication, and mistakes, leading to cleaner and more minimal code.

One key technical highlight is the use of a CLAUDE.md file to apply these guidelines across projects, making it easy to adopt and customize the principles for specific use cases.

In summary, the multica-ai/andrej-karpathy-skills repository provides a valuable resource for improving coding practices, and its guidelines can be applied to various projects to promote better coding habits: By giving your coding assistant clear goals and guidelines, you can unlock its full potential and work more efficiently.

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🧠 Channel: https://t.me/GithubRe

⚡ dotnet/skills is making waves. Here's the full picture.

🔗 https://github.com/dotnet/skills
📝 Repository for skills to assist AI coding agents with .NET and C#
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The dotnet/skills repository is a curated set of core skills and custom agents for coding agents. It provides a range of plugins, including dotnet, dotnet-data, dotnet-diag, and more, each with its own set of skills for handling common .NET coding tasks.

To use these skills, you can install them via the Copilot CLI or Claude Code by adding the dotnet/skills marketplace and installing the desired plugin. You can also install them in VS Code or VS Code Insiders by enabling plugin support and adding the dotnet/skills marketplace to your settings.

Additionally, this repository is a Cursor plugin marketplace, allowing you to discover and install published plugins directly in Cursor. The skills in this repository follow the agentskills.io open standard and are compatible with OpenAI Codex.

The target audience for this repository includes .NET developers, coding agents, and anyone looking to leverage the power of AI and ML in their development workflow.

One key takeaway: With dotnet/skills, you can supercharge your .NET development with AI-powered coding agents and take your productivity to the next level.

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🧠 Channel: https://t.me/GithubRe

⚡ ChromeDevTools/chrome-devtools-mcp is making waves. Here's the full picture.

🔗 https://github.com/ChromeDevTools/chrome-devtools-mcp
📝 Chrome DevTools for coding agents
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The ChromeDevTools/chrome-devtools-mcp repository on GitHub provides a Model-Context-Protocol (MCP) server that enables coding agents like Antigravity, Claude, and Copilot to control and inspect a live Chrome browser. This allows for reliable automation, in-depth debugging, and performance analysis.

Key features include:
- Advanced browser debugging: Analyze network requests, take screenshots, and check browser console messages.
- Performance insights: Record traces and extract actionable performance insights using Chrome DevTools.
- Reliable automation: Automate actions in Chrome using puppeteer and automatically wait for action results.

To get started, add the following config to your MCP client:

{
  "mcpServers": {
    "chrome-devtools": {
      "command": "npx",
      "args": ["-y", "chrome-devtools-mcp@latest"]
    }
  }
}

The project supports various MCP clients, including Antigravity, Claude, Copilot, and more, with detailed installation guides provided.

One-liner takeaway: Supercharge your coding agents with the power of Chrome DevTools using ChromeDevTools/chrome-devtools-mcp!

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🧠 Channel: https://t.me/GithubRe

⚡ mukul975/Anthropic-Cybersecurity-Skills is making waves. Here's the full picture.

🔗 https://github.com/mukul975/Anthropic-Cybersecurity-Skills
📝 754 structured cybersecurity skills for AI agents · Mapped to 5 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND & NIST AI RMF · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 26 security domains · Apache 2.0
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The Anthropic Cybersecurity Skills GitHub repository is a game-changer for AI agents in the cybersecurity space. It provides a massive library of 754 production-grade cybersecurity skills across 26 security domains, all mapped to five industry frameworks (MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, and NIST AI RMF). This allows AI agents to gain expert-level guidance in seconds, bridging the cybersecurity workforce gap.

To get started, users can simply clone the repository or use npx skills add mukul975/Anthropic-Cybersecurity-Skills for a quick setup. The repository is compatible with various AI platforms, including Claude Code, GitHub Copilot, and OpenAI Codex CLI.

The skills are structured in a YAML frontmatter format for easy discovery and a Markdown body for step-by-step execution. Each skill includes references, scripts, and assets to provide deep technical context.

The repository is perfect for security professionals, developers, and enterprise teams looking to enhance their AI agents' capabilities. With this library, AI agents can perform tasks such as threat hunting, incident response, and vulnerability management with ease.

In a nutshell, the Anthropic Cybersecurity Skills repository is a powerful tool that gives AI agents the security skills of a senior analyst, and that's a huge deal!

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🧠 Channel: https://t.me/GithubRe