🌟 koala73/worldmonitor caught my eye on GitHub Trending today.

🔗 https://github.com/koala73/worldmonitor
📝 Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
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The World Monitor is a real-time global intelligence dashboard that aggregates news, tracks geopolitical events, and monitors infrastructure using AI. Its key features include 500+ curated news feeds, a dual map engine, and a Country Instability Index (CII).

To use World Monitor, you can git clone the repository, run npm install, and start the development server with npm run dev. The app can be accessed at localhost:3000.

World Monitor is built using a tech stack that includes TypeScript, Vite, and Tauri 2, with a focus on AI/ML using Ollama and Groq. It provides programmatic access through an MCP server, REST API, and CLI, as well as SDKs for Python, Ruby, and Go.

The project is licensed under AGPL-3.0-only and is open to contributions. To contribute, run npm run typecheck and npm run build:full to ensure your changes are valid.

In summary, World Monitor is an open-source, AI-powered dashboard for global intelligence - and with its extensive features and accessible codebase, you can monitor the world, in real-time, from your fingertips.

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🧠 Channel: https://t.iss.one/GithubRe

🎯 bojieli/ai-agent-book landed on trending. Worth a proper look.

🔗 https://github.com/bojieli/ai-agent-book
📝 《深入理解 AI Agent：设计原理与工程实践》（李博杰 著）开源主仓库：全书正文、编译版 PDF 与按章配套代码
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The bojieli/ai-agent-book GitHub repository offers a comprehensive guide to understanding AI Agents, focusing on the core formula: Agent = LLM + Context + Tools. This open-source project includes a 10-chapter book, 88 accompanying projects, and support for 5 languages. The book covers topics from the basics of agents to advanced engineering practices, including context engineering, user memory, tools, coding agents, and evaluation.

Key features include:
- 10 chapters of in-depth content, ranging from foundational knowledge to production-level practices.
- 88 projects that complement the chapters, with over 70 being independently runnable.
- Support for 5 languages: Chinese, Taiwanese, English, Tamil, and Vietnamese.

The technical highlights of this project involve:
- A detailed exploration of Agent = LLM + Context + Tools, breaking down the components and their integration.
- Discussion on context engineering, including KV Cache, prompt engineering, and context compression.
- Examination of user memory and knowledge bases, covering user memory, RAG, structured indexes, and knowledge graphs.

This project is suitable for a wide range of audiences, from beginners looking to understand the basics of AI Agents to advanced practitioners seeking to improve their skills in AI engineering.

To get started, one can directly download the PDF or EPUB versions of the book or explore the repository for specific code projects and chapters.

In summary, bojieli/ai-agent-book is an invaluable resource for anyone interested in AI Agents, providing a thorough and hands-on approach to understanding and implementing these technologies.
The takeaway: Empower your understanding of AI Agents with bojieli/ai-agent-book, and unlock the potential of AI engineering.

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🧠 Channel: https://t.iss.one/GithubRe

🚀 Meet tirth8205/code-review-graph: a gem from today's GitHub trending list.

🔗 https://github.com/tirth8205/code-review-graph
📝 Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
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Code Review Graph is a tool that helps AI coding assistants review code smarter, not harder. It builds a structural map of your codebase using Tree-sitter and tracks changes incrementally, providing your AI assistant with precise context via MCP so it only reads what matters.

Key features include install, build, and uninstall commands, as well as support for multiple AI coding platforms like Codex, Claude Code, and GitHub Copilot. The tool also includes blast-radius analysis to minimize the files your AI assistant needs to read.

To get started, simply run

pip install code-review-graph

and

code-review-graph install

to auto-detect and configure your AI coding tools.

Code Review Graph is designed for developers who want to optimize their code review process and reduce token waste. With its broad language coverage, including support for Python, JavaScript, and Ruby, as well as Jupyter notebooks, it's an essential tool for any developer looking to streamline their workflow.

The takeaway: code-review-graph is a game-changer for AI-assisted code reviews, cutting token waste by up to 528x and making your coding life easier!

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🧠 Channel: https://t.iss.one/GithubRe

🔥 ayghri/i-have-adhd is trending — and it deserves your attention.

🔗 https://github.com/ayghri/i-have-adhd
📝 A skill for your coding agent to stop it from burying the answer. ADHD-friendly output.
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The i-have-adhd GitHub repository offers a unique solution for individuals with ADHD, providing a coding assistant skill that streamlines outputs and eliminates unnecessary information.

To get started, you can install the skill using Claude Code or Codex by running the following commands:

claude plugin marketplace add ayghri/i-have-adhd
claude plugin install i-have-adhd@i-have-adhd

or

codex plugin marketplace add ayghri/i-have-adhd --ref main
codex plugin add i-have-adhd@i-have-adhd

The key features of this skill include leading with the next action, numbering multi-step tasks, and ending with a concrete next step. It also suppresses tangents, restates the state every turn, and provides specific time estimates.

The repository is suitable for developers and individuals with ADHD who want to improve their productivity and focus. It's technically built with a set of 10 rules that can be customized by forking the repository and editing the `SKILL.md` file.

Takeaway: This skill helps you get straight to the point and take action, making it a valuable tool for anyone looking to boost their productivity!

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🧠 Channel: https://t.iss.one/GithubRe

🚀 Meet earthtojake/text-to-cad: a gem from today's GitHub trending list.

🔗 https://github.com/earthtojake/text-to-cad
📝 A collection of agent skills for CAD, robotics and hardware design
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The CAD Skills library is a game-changer for CAD, robotics, and hardware design agents. It offers a range of skills for generating, inspecting, and handing off CAD and robot-description artifacts. With text-to-cad, you can create and edit CAD models from plain-language or image requests, and export them to various formats like STEP, STL, and 3MF. The library also includes skills for CAD viewing, robotics, and simulation. To get started, you can install the library using the Skills CLI with the command npx skills install earthtojake/text-to-cad. The library is suitable for developers, designers, and engineers who want to streamline their CAD and robotics workflows. Overall, CAD Skills is a powerful tool that can help you design, simulate, and manufacture with ease - and that's a recipe for innovation!

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🧠 Channel: https://t.iss.one/GithubRe

🚀 Meet 1jehuang/jcode: a gem from today's GitHub trending list.

🔗 https://github.com/1jehuang/jcode
📝 The most intelligent agent harness for code
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The jcode GitHub repository offers a next-generation coding agent harness designed for multi-session workflows, infinite customizability, and high performance. Its key features include a human-like memory system that automatically recalls relevant information, and a highly efficient architecture that minimizes RAM usage and boot time.

To use jcode, you can install it via a simple script on macOS, Linux, or Windows. The installation process is straightforward, and detailed instructions are provided in the repository.

From a technical standpoint, jcode stands out for its optimized performance and resource efficiency. It boasts significantly lower RAM usage and faster boot times compared to other tools like pi, Codex CLI, and GitHub Copilot CLI.

The target audience for jcode appears to be developers and power users seeking a high-performance, customizable coding agent that can handle complex workflows and provide intelligent memory recall.

In short, jcode is a game-changer for coding workflows - it's fast, efficient, and intelligent.

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🧠 Channel: https://t.iss.one/GithubRe