🔍 Deep-diving into byoungd/English-level-up-tips — fresh off the trending list.

🔗 https://github.com/byoungd/English-level-up-tips
📝 An advanced guide to learn English which might benefit you a lot 🎉 . 人生进阶指南 离谱的人生 离谱的英语学习指南/英语学习教程/英语学习/学英语
──────────────────────────────

The English-level-up-tips GitHub repository is a comprehensive guide to learning English, created with the goal of helping individuals improve their language skills. The repository is divided into several chapters, each focusing on a different aspect of language learning, such as understanding, vocabulary, listening, reading, speaking, and writing.

The repository also features an AI chapter that has been updated to 2026, which provides a systematic approach to using AI in language learning, including how to use Gemini as the main engine and how to design a training loop that incorporates ChatGPT, Claude, Perplexity, and DeepL Write.

The guide is designed to be a valuable resource for anyone looking to improve their English skills, and it is available to read online on various platforms, including GitHub Pages and GitBook.

The creator of the repository, byoungd, has made it available under a Creative Commons license, and it is free to use and share.

In short, this repository is an excellent resource for English language learners, and its AI-powered approach makes it a standout in the field - so, learn English like you mean it.

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

⚡ DeusData/codebase-memory-mcp is making waves. Here's the full picture.

🔗 https://github.com/DeusData/codebase-memory-mcp
📝 High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
──────────────────────────────

The codebase-memory-mcp GitHub repository is home to the fastest and most efficient code intelligence engine for AI coding agents. This engine is capable of full-indexing an average repository in milliseconds and answering structural queries in under 1ms.

Key features include high-quality parsing through tree-sitter AST analysis across 158 languages, Hybrid LSP semantic type resolution for 9 languages, and a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links.

Usage is straightforward, with a one-line install command for macOS, Linux, and Windows, and a simple install command to configure MCP server entries and instruction files for 11 coding agents.

Technical highlights include a RAM-first pipeline with LZ4 compression, in-memory SQLite, and fused Aho-Corasick pattern matching, resulting in extreme indexing speed and low memory usage.

This project is suitable for developers and researchers looking to improve their code exploration and development workflow.

In a nutshell, codebase-memory-mcp is a game-changer for coding agents, offering unparalleled speed and efficiency - Index your codebase in milliseconds and supercharge your coding experience!

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

💡 NousResearch/hermes-agent just hit the trending charts — here's why it matters.

🔗 https://github.com/NousResearch/hermes-agent
📝 The agent that grows with you
──────────────────────────────

Hermes Agent is a self-improving AI agent that learns from experience, improves its skills, and builds a deep understanding of its users. With a built-in learning loop, it creates skills from experience, improves them during use, and searches its own past conversations. Key features include:
- A real terminal interface with multiline editing and conversation history
- Cross-platform support for Telegram, Discord, Slack, WhatsApp, Signal, and CLI
- Scheduled automations with a built-in cron scheduler
- Support for various models from different providers, including Nous Portal, OpenRouter, and Hugging Face

To get started, users can install Hermes Agent using a curl command or a PowerShell script, and then configure the agent using the hermes setup command. The agent can be run on a variety of platforms, including Linux, macOS, Windows, and cloud infrastructure.

With its flexible architecture and user-friendly interface, Hermes Agent is designed for users who want a powerful and customizable AI assistant. Whether you're a developer, researcher, or simply looking for a smarter way to interact with AI, Hermes Agent is definitely worth checking out.
One-liner takeaway: With Hermes Agent, you can have a personalized AI assistant that learns and adapts to your needs, all while being easy to use and customize.

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

🌟 affaan-m/ECC caught my eye on GitHub Trending today.

🔗 https://github.com/affaan-m/ECC
📝 The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
──────────────────────────────

The ECC GitHub repository is an innovative project that introduces an agent harness operating system designed for agentic work. At its core, ECC is a comprehensive system that encompasses skills, instincts, memory optimization, continuous learning, security scanning, and research-first development. This system is built on top of real-world multi-harness engineering workflows and is compatible with various AI agent harnesses, including Codex, Claude Code, and GitHub Copilot.

ECC provides a range of features, including production-ready agents, skills, hooks, rules, and legacy command shims, all of which have been developed and refined over 10+ months of intensive daily use in building real products. The repository is well-documented, with guides available in multiple languages, including English, Português (Brasil), 简体中文, and many others.

The ECC system is designed to be language-agnostic, supporting a wide range of programming languages, including TypeScript, Python, Go, Java, and Perl. It also features a cross-harness architecture, allowing for seamless integration with different AI agent harnesses.

The repository has a strong focus on security, with features like AgentShield and security scanning to protect against potential threats. Additionally, ECC has a community-driven approach, with a Discord community and GitHub App available for users to interact with the project and its maintainers.

Overall, the ECC repository is an exciting project that has the potential to revolutionize the way we work with AI agents. With its comprehensive features, language-agnostic design, and strong focus on security, ECC is an excellent choice for developers and researchers looking to harness the power of AI in their work.

One-liner takeaway: ECC is a game-changing agent harness operating system that's poised to transform the way we work with AI agents, and it's available now on GitHub.

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

💡 calesthio/OpenMontage just hit the trending charts — here's why it matters.

🔗 https://github.com/calesthio/OpenMontage
📝 World's first open-source, agentic video production system. 12 pipelines, 52 tools, 500+ agent skills. Turn your AI coding assistant into a full video production studio.
──────────────────────────────

Meet OpenMontage, the first open-source, agentic video production system. It's designed to turn your AI coding assistant into a full video production studio, where you can describe what you want in plain language and let the agent handle research, scripting, 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 OpenMontage to create image-based videos or real videos using free stock footage and open archives.

To get started, you'll need to install Python 3.10+, FFmpeg, and Node.js 18+. Then, clone the repository, run make setup, and open the project in your AI coding assistant.

OpenMontage is suitable for a wide range of users, from video producers to marketers and educators. It's a powerful tool for creating high-quality videos without requiring extensive video production experience.

With OpenMontage, you can create stunning videos like "SIGNAL FROM TOMORROW" or "THE LAST BANANA" with minimal cost and effort. The system is designed to be flexible and customizable, allowing you to add API keys for various tools and services to unlock more features.

In summary, OpenMontage is a game-changer for video production, and its community-driven approach ensures that it will continue to evolve and improve over time. So, why not give it a try and see what you can create? OpenMontage is the future of video production, and it's available now.

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

🔍 Deep-diving into ZhuLinsen/daily_stock_analysis — fresh off the trending list.

🔗 https://github.com/ZhuLinsen/daily_stock_analysis
📝 LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.
──────────────────────────────

Daily Stock Analysis is an open-source project that provides a comprehensive daily stock analysis system. The system utilizes AI models to analyze stocks and provide decision-making reports.

Key Features:
- AI decision-making reports
- Multi-market data aggregation
- Web and desktop workspaces
- Agent strategy inquiry
- Intelligent import and completion
- Automation and push notifications

The system supports various AI models, including Anspire, AIHubMix, and OpenAI. It also aggregates data from multiple markets, including A-share, Hong Kong stocks, US stocks, and more.

Technical Highlights:
- The system uses Python 3.10+ and supports Docker and GitHub Actions.
- It provides a web interface for configuration management, task monitoring, and manual analysis.

Audience:
- The project is suitable for individual investors, financial analysts, and researchers who want to utilize AI-powered stock analysis.

To get started, users can fork the repository and configure the secrets, or they can use the client configuration tutorial.

python main.py --debug

One-liner Takeaway: Daily Stock Analysis is a powerful open-source tool that leverages AI to provide comprehensive daily stock analysis and decision-making reports, making it an excellent resource for investors and researchers alike.

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

💡 apple/container just hit the trending charts — here's why it matters.

🔗 https://github.com/apple/container
📝 A tool for creating and running Linux containers using lightweight virtual machines on a Mac. It is written in Swift, and optimized for Apple silicon.
──────────────────────────────

The apple/container GitHub repo is home to a powerful tool that lets you create and run Linux containers on your Mac, leveraging the power of Apple silicon. Written in Swift, this tool is optimized for performance and supports OCI-compatible container images, making it easy to pull and run images from standard container registries.

To get started, you'll need a Mac with Apple silicon and macOS 26 or later. The container tool uses the Containerization Swift package for low-level management.

You can start, stop, and update the container system service using simple commands. The repo also provides a guided tour and technical overview to help you understand the tool's capabilities.

The project is under active development, and contributions are welcome. Whether you're a seasoned developer or just curious, container is definitely worth exploring. Here's a simple example of how to start the system service:

container system start

One-liner takeaway: Experience the power of Linux containers on your Mac with the apple/container tool, and take your development to the next level!

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

⚡ interviewstreet/hiring-agent is making waves. Here's the full picture.

🔗 https://github.com/interviewstreet/hiring-agent
📝 AI agent to evaluate and score resumes.
──────────────────────────────

The Hiring Agent is a Resume-to-Score pipeline that extracts structured data from PDFs, enriches it with GitHub signals, and outputs a fair, explainable evaluation. It's designed to be used by recruiters, hiring managers, or anyone looking to streamline their candidate evaluation process.

The pipeline works by first converting a resume PDF to Markdown-like text using pymupdf_rag.py and pdf.py. It then uses a local or hosted Large Language Model (LLM) to extract sectioned JSON data. The data is further enriched with GitHub profile and repository signals using github.py.

The evaluation process involves running a strict-scored evaluation with fairness constraints using evaluator.py. The final output includes category scores, evidence, bonus points, and deductions.

To use the Hiring Agent, you'll need to install the required dependencies using pip install -r requirements.txt and set up your environment variables. You can choose to use either the Ollama or Gemini LLM provider.

One of the key technical highlights of the Hiring Agent is its use of Pydantic schemas and LLM provider interfaces in models.py. The pipeline also includes a set of Jinja templates for extraction and scoring, which can be found in the prompts/ directory.

Overall, the Hiring Agent is a powerful tool for anyone looking to automate their candidate evaluation process. With its flexible architecture and easy-to-use interface, it's an ideal solution for recruiters and hiring managers alike.

So, what are you waiting for? Automate your hiring process with the Hiring Agent and start finding the best candidates for your team!

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

🔍 Deep-diving into JCodesMore/ai-website-cloner-template — fresh off the trending list.

🔗 https://github.com/JCodesMore/ai-website-cloner-template
📝 Clone any website with one command using AI coding agents
──────────────────────────────

Ai Website Cloner Template is an innovative, open-source project that enables you to reverse-engineer any website into a clean, modern Next.js codebase using AI coding agents. This template is designed to work with a variety of AI agents, with Claude Code being the recommended choice for the best results.

To get started, simply create a copy of the template repository, install the dependencies, start your AI agent, and run the /clone-website skill with the target URL. The template will then inspect the site, extract design tokens and assets, write component specs, and dispatch parallel builders to reconstruct every section.

The project features a multi-phase pipeline that includes reconnaissance, foundation, component specs, parallel build, and assembly & QA. It supports various AI coding agents, including Claude Code, Codex CLI, and GitHub Copilot, among others.

The template is ideal for platform migration, lost source code, and learning purposes. However, it is not intended for phishing or impersonation, passing off someone's design as your own, or violating terms of service.

In terms of technical highlights, the project uses Next.js 16, React 19, and TypeScript strict, along with shadcn/ui and Tailwind CSS v4 for styling.

Overall, the Ai Website Cloner Template is a powerful tool that can help you create a modern, clean codebase for any website, and its potential impact on the web development community is significant.

You can clone any website with just one command: /clone-website - the future of web development just got a whole lot easier.

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe

📌 Spotted on GitHub Trending: revfactory/harness — let's break it down.

🔗 https://github.com/revfactory/harness
📝 A meta-skill that designs domain-specific agent teams, defines specialized agents, and generates the skills they use.
──────────────────────────────

The revfactory/harness GitHub repository is home to Harness, a team-architecture factory for Claude Code that revolutionizes how complex tasks are approached by decomposing them into coordinated teams of specialized agents. With Harness, users can simply prompt Build a harness for this project and see their domain description transformed into an agent team and the skills they utilize, chosen from six pre-defined team-architecture patterns: Pipeline, Fan-out/Fan-in, Expert Pool, Producer-Reviewer, Supervisor, and Hierarchical Delegation.

Key Features include agent team design, skill generation with Progressive Disclosure for efficient context management, orchestration for inter-agent data passing and error handling, and validation through trigger verification, dry-run testing, and comparison tests. The plugin structure is well-organized, with a clear plugin.json manifest and skill directories for easy installation and use.

To start, users can install Harness via the marketplace with /plugin marketplace add revfactory/harness followed by /plugin install harness@harness-marketplace, or directly as a global skill. The workflow involves domain analysis, team architecture design, agent definition generation, skill generation, integration, and validation.

Harness is particularly useful for a variety of projects and tasks, including deep research, website development, webtoon/comic production, YouTube content planning, code review, technical documentation, data pipeline design, and marketing campaigns. It coexists with other tools like Archon for deterministic runtime configurations and meta-harness for Codex runtime, offering a comprehensive approach to team architecture and workflow management.

The takeaway? Harness is a game-changer for anyone working with complex tasks and agent teams, offering +60% average quality improvement and a 100% win rate in controlled experiments. So why not give it a try and see how Harness can transform your workflow? Build a harness for your next project and experience the power of structured team architecture!

──────────────────────────────
🧠 Channel: https://xn--r1a.website/GithubRe