📌 Spotted on GitHub Trending: affaan-m/ECC — let's break it down.

🔗 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.
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The ECC repository on GitHub is a comprehensive system for agentic work, built from real-world multi-harness engineering workflows. It's not just about configurations, but a complete system that includes skills, instincts, memory optimization, continuous learning, security scanning, and research-first development. ECC works across various AI agent harnesses, such as Codex, Claude Code, Cursor, and OpenCode.

The system is designed to be production-ready, with features like token optimization, memory persistence, and continuous learning. It also includes a range of skills, hooks, rules, and configurations to support different use cases.

ECC v2.0.0-rc.1

is the latest release, which adds a public Hermes operator story and a reusable layer for building custom operators.

ECC is suitable for data scientists, engineers, and developers who want to build and deploy AI-powered agents for various tasks. The repository has a large community of contributors and users, with over 182K+ stars and 28K+ forks. The project is open-source, with a permissive MIT license, and is actively maintained by its creator, affaan-m.

Overall, ECC is a powerful tool for building and deploying AI agents, with a strong focus on community, security, and continuous learning. With its comprehensive features and large community, ECC is an ideal choice for anyone looking to build and deploy AI-powered agents. Here's the takeaway: Build intelligent agents with ECC and unlock the full potential of AI.

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🚀 Meet hardikpandya/stop-slop: a gem from today's GitHub trending list.

🔗 https://github.com/hardikpandya/stop-slop
📝 A skill file for removing AI tells from prose
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The Stop Slop GitHub repository offers a skill for removing AI tells from prose, teaching large language models like Claude to catch and remove predictable phrases, structures, and rhythms.

Key features include a set of references with phrases and structures to avoid, along with examples of before/after transformations. To use, simply add the skill to Claude or upload the SKILL.md and reference files to a project's knowledge base.

From a technical standpoint, the repository is structured with clear instructions in SKILL.md and includes reference files like phrases.md and structures.md.

The target audience appears to be developers and writers looking to refine AI-generated content.

With its scoring system, which rates directness, rhythm, trust, authenticity, and density, this skill helps you refine your writing - and that's a game-changer for AI writing: make it sound human, or make it stop.

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🚀 Meet DataTalksClub/data-engineering-zoomcamp: a gem from today's GitHub trending list.

🔗 https://github.com/DataTalksClub/data-engineering-zoomcamp
📝 Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼
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The Data Engineering Zoomcamp is a free 9-week course that teaches data engineering fundamentals by building an end-to-end data pipeline from scratch. With hands-on experience using industry-standard tools and best practices, students gain a deep understanding of data engineering concepts.

The course includes structured modules, hands-on workshops, and a final project to reinforce learning. Key features cover data ingestion, workflow orchestration, data warehousing, analytics engineering, and more.

To get started, students can enroll in the 2026 cohort or opt for self-paced learning by watching course videos, joining the Slack community, and referring to the FAQ document.

The course is suitable for those with basic coding experience, familiarity with SQL, and some experience with Python. No prior data engineering experience is necessary.

The Data Engineering Zoomcamp is perfect for anyone looking to break into data engineering, with a supportive community, expert instructors, and a comprehensive curriculum.
Join the Data Engineering Zoomcamp and transform your career in just 9 weeks!

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🔥 codecrafters-io/build-your-own-x is trending — and it deserves your attention.

🔗 https://github.com/codecrafters-io/build-your-own-x
📝 Master programming by recreating your favorite technologies from scratch.
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The codecrafters-io/build-your-own-x GitHub repository is a treasure trove of step-by-step guides for building various technologies from scratch. It covers a wide range of topics, including 3D renderers, AI models, blockchains, bots, databases, and more. With tutorials in multiple programming languages, such as C++, Java, Python, and JavaScript, this resource is suitable for developers of all levels. The guides are designed to be hands-on, allowing you to learn by doing, and are perfect for anyone looking to gain a deeper understanding of how different technologies work. Whether you're a beginner or an experienced developer, this repository has something for everyone. So, get ready to build your own and take your skills to the next level: building is learning.

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🔍 Deep-diving into harry0703/MoneyPrinterTurbo — fresh off the trending list.

🔗 https://github.com/harry0703/MoneyPrinterTurbo
📝 利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.
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MoneyPrinterTurbo is a powerful tool that generates videos with AI-generated scripts, subtitles, and background music. It supports multiple video sizes, batch generation, and customizable settings. The project has a clear and maintainable MVC architecture and is easy to use through its Web and API interfaces.

Key features include:

* AI-generated video scripts and subtitles
* Support for multiple video sizes and formats
* Batch generation and customizable settings
* Integration with various AI models and services

The project is suitable for developers and non-technical users alike, with a simple and intuitive interface. It's also highly customizable, allowing users to tailor the output to their specific needs.

Some technical highlights include:

* Support for multiple AI models and services
* ImageMagick integration for image processing
* ffmpeg integration for video processing

To get started, users can follow the quick start guide, which includes instructions for installing and running the project on various platforms.

In summary, MoneyPrinterTurbo is a powerful and flexible tool for generating videos with AI-generated content. With its easy-to-use interface and customizable settings, it's an ideal solution for anyone looking to create high-quality videos quickly and efficiently. Give it a try and start creating your own videos today!

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🌟 microsoft/markitdown caught my eye on GitHub Trending today.

🔗 https://github.com/microsoft/markitdown
📝 Python tool for converting files and office documents to Markdown.
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MarkItDown is a lightweight Python utility for converting various files to Markdown, ideal for use with Large Language Models (LLMs) and text analysis pipelines. It supports conversion from multiple file formats, including PDF, PowerPoint, Word, Excel, images, audio, HTML, and more. The goal is to preserve important document structure and content as Markdown, making it easily consumable by text analysis tools.

Key features include:
- Support for multiple file formats
- Preserves document structure and content as Markdown
- Optional dependencies for activating various file formats
- Plugin support for adding new features, such as OCR

To use MarkItDown, you can install it via pip: pip install 'markitdown[all]'. Then, simply run the command markitdown path-to-file.pdf > document.md to convert a file.

MarkItDown also integrates with Azure Content Understanding and Azure Document Intelligence for higher-quality conversions. Additionally, it supports Large Language Models for image descriptions.

The project welcomes contributions and has adopted the Microsoft Open Source Code of Conduct.

In short, MarkItDown is a powerful tool for converting files to Markdown, and its flexibility and customization options make it an ideal choice for a variety of use cases. Convert your files to Markdown with ease using MarkItDown – your text analysis pipelines will thank you!

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⚡ D4Vinci/Scrapling is making waves. Here's the full picture.

🔗 https://github.com/D4Vinci/Scrapling
📝 🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!
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Scrapling is an adaptive web scraping framework that simplifies the process of extracting data from websites. Its key features include selection methods, fetchers, and spiders that enable users to scale up to concurrent, multi-session crawls with pause/resume and automatic proxy rotation. The framework is designed to handle website changes and anti-bot systems, ensuring that your data extraction efforts are not disrupted.

To use Scrapling, you can start by installing the library and then using its various components, such as the Fetcher and Spider classes, to fetch and parse web pages. For example:

from scrapling.fetchers import Fetcher
p = Fetcher.fetch('https://example.com', headless=True, network_idle=True)
products = p.css('.product', auto_save=True)

Scrapling is suitable for both beginners and experienced users, providing an easy-to-use interface for simple scraping tasks and advanced features for large-scale crawls. Whether you're a web scraper, data scientist, or just someone looking to extract data from websites, Scrapling has something for everyone. With its blazing fast performance, real-time stats, and streaming capabilities, Scrapling is the perfect tool for anyone looking to extract data from the web.
Scrapling: where web scraping meets simplicity - try it and scrape like a pro!

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