Github Top Repositories

🌟 hardikpandya/stop-slop caught my eye on GitHub Trending today. 🔗 https://github.com/hardikpandya/stop-slop 📝 A skill file for removing AI tells from prose ────────────────────────────── The Stop Slop GitHub repository is a skill designed to remove AI tells from prose, making your writing sound more human. The key features include a set of rules and references that help catch and remove predictable phrases, structures, and rhythms. To use it, simply add the folder as a skill or upload the SKILL.md and reference files to your project knowledge. You can also include SKILL.md in your system prompt for API calls. The repository catches various patterns such as banned phrases, structural clichés, and sentence-level rules, and even provides a scoring system to rate your writing. This repository is perfect for writers and developers looking to improve their writing skills and make their content sound more authentic. In a nutshell, Stop Slop helps you write like a human, not a robot - so stop the slop and start writing. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 affaan-m/ECC just hit the trending charts — here's why it matters. 🔗 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. ────────────────────────────── ECC is an open-source, harness-native operator system for agentic work, built from real-world multi-harness engineering workflows. It's designed to work across various AI agent harnesses, including Codex, Claude Code, Cursor, OpenCode, and more. The system provides a complete set of features, including skills, instincts, memory optimization, continuous learning, security scanning, and research-first development. To get started with ECC, you can follow the HERMES setup guide and review the release notes and cross-harness architecture documentation. Key features include: - Token optimization - Memory persistence - Continuous learning - Verification loops - Parallelization - Subagent orchestration ECC is suitable for developers, engineers, and researchers working with AI agent harnesses. Technical highlights include support for multiple programming languages, such as Python, Java, Go, and TypeScript. In summary, ECC is a powerful tool for building and managing AI agent workflows, and its open-source nature makes it a great choice for anyone looking to automate and optimize their workflows - ECC is the future of agentic work, and the future is now. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 DigitalPlatDev/FreeDomain caught my eye on GitHub Trending today. 🔗 https://github.com/DigitalPlatDev/FreeDomain 📝 DigitalPlat FreeDomain: Free Domain For Everyone ────────────────────────────── DigitalPlat FreeDomain is a platform that offers free domain names to individuals and organizations, promoting a more accessible web. The goal is to make the internet an open space where everyone can have their own online presence, regardless of budget. Key features include free domain registration with various extensions like .DPDNS.ORG and .US.KG, and the freedom to host with your preferred DNS provider. To get started, simply visit the DigitalPlat FreeDomain Dashboard and follow the tutorial. From a technical standpoint, the project has grown significantly, now supporting over 500,000 domains. The founder, Edward Hsing, shares the story of how this started as a small DNS experiment and evolved into a reliable service. The target audience is anyone looking to establish an online presence without the burden of domain costs. Whether you're a developer, blogger, or just starting out, DigitalPlat FreeDomain is a great option. In short, DigitalPlat FreeDomain is a game-changer for those who want to create a website without breaking the bank - Claim your free domain and start building your online presence today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 Crosstalk-Solutions/project-nomad just hit the trending charts — here's why it matters. 🔗 https://github.com/Crosstalk-Solutions/project-nomad 📝 Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere. ────────────────────────────── Project N.O.M.A.D. is a self-contained, offline-first knowledge and education server that empowers users with critical tools and AI, anytime, anywhere. Key features include an AI chat with knowledge base, information library, education platform, offline maps, data tools, and notes. To get started, users can follow the Quick Install guide for Debian-based operating systems. For more control, advanced users can use the Docker Compose template to customize their installation. Technical highlights of Project N.O.M.A.D. include its management UI and API, which orchestrate a collection of containerized tools and resources via Docker. The project is suitable for users who want to access knowledge and education resources offline, including students, researchers, and individuals in areas with limited internet connectivity. The project is licensed under the Apache License 2.0 and has a growing community with resources like a website, Discord channel, and benchmark leaderboard. In a nutshell, Project N.O.M.A.D. is the ultimate offline companion for knowledge seekers - empowering minds, anywhere. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 Biohub/esm landed on trending. Worth a proper look. 🔗 https://github.com/Biohub/esm 📝 No description. ────────────────────────────── The Biohub/esm GitHub repository presents a groundbreaking world model of protein biology, leveraging the latest advancements in Evolutionary Scale Modeling (ESM). This comprehensive system comprises three primary components: ESMC, ESMFold2, and ESM Atlas. ESMC is a state-of-the-art protein language model trained on billions of protein sequences, allowing it to learn and represent the rules of protein biology. ESMFold2 builds upon ESMC and is a state-of-the-art structure prediction model that can predict high-resolution, all-atom 3D protein structures directly from amino acid sequences. The ESM Atlas is a vast map of 6.8 billion proteins, organized according to the internal world model of ESMC, enabling the prediction of over one billion structures. These tools can be utilized through the Biohub Platform or by running the models locally with Hugging Face. The repository provides extensive documentation, including tutorials and preprints, to facilitate understanding and usage. The target audience includes researchers, scientists, and developers interested in protein biology, structure prediction, and world modeling. Here is a simple example of running ESMC locally:

import torch
from transformers import AutoModelForMaskedLM, AutoTokenizer

# example GFP sequence
sequences = ["MSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPTLVTTFSYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTLVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITHGMDELYK"]

model = AutoModelForMaskedLM.from_pretrained(
    "Biohub/ESMC-6B",
    device_map="auto",
).eval()
tokenizer = AutoTokenizer.from_pretrained("Biohub/ESMC-6B")

inputs = tokenizer(sequences, return_tensors="pt", padding=True)
inputs = {k: v.to(model.device) for k, v in inputs.items()}
with torch.inference_mode():
    output = model(**inputs)

To get started, simply install the esm library and import the necessary modules. With Biohub/esm, unlock the power of world modeling in protein biology and discover new frontiers in protein structure prediction and design. The future of protein biology is here, and it's being modeled with unprecedented accuracy. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 byoungd/English-level-up-tips landed on trending. Worth a proper look. 🔗 https://github.com/byoungd/English-level-up-tips 📝 An advanced guide to learn English which might benefit you a lot 🎉 . 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, dedicated to the author's past love, W. This project aims to provide a detailed and advanced guide to help individuals improve their English skills. The guide covers various aspects of the English language, including understanding, vocabulary, listening, reading, speaking, and writing. It also features a chapter on AI and its application in language learning. The guide is suitable for anyone looking to improve their English skills, from beginners to advanced learners. It's a valuable resource for those who want to learn English in a natural and enjoyable way. Key features of the guide include its comprehensive coverage of the English language, its use of AI in language learning, and its focus on making learning English a fun and rewarding experience. The guide is available for online reading on various platforms, including GitHub Pages, GitBook, and Zhihu. In short, the English-level-up-tips guide is a must-have resource for anyone looking to improve their English skills, and with dedication and practice, you can master the English language and unlock a world of new opportunities. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet galilai-group/stable-worldmodel: a gem from today's GitHub trending list. 🔗 https://github.com/galilai-group/stable-worldmodel 📝 A platform for reproducible world model research and evaluation ────────────────────────────── The stable-worldmodel repository provides a unified platform for world model research and evaluation. It offers a single interface for data collection, training, and evaluation with model-predictive control across various environments. The repository includes reference implementations of common baselines and planning solvers, allowing researchers to focus on their core contributions. The library supports multiple data formats, including lance, hdf5, folder, video, and lerobot, and provides tools for format conversion and benchmarking. It also features a large suite of environments, including those from the DeepMind Control Suite, Gymnasium, and OGBench, with factors of variation for evaluating zero-shot generalization. To get started, users can install the library via PyPI and follow the quick start guide to collect data, train a world model, and evaluate it using model-predictive control. The repository is in active development, with APIs subject to change between minor versions. The stable-worldmodel library is designed for researchers and developers working on world models, and its unified interface and reference implementations make it an ideal choice for those looking to advance the state-of-the-art in this field. With stable-worldmodel, the world is your model, and the possibilities are endless. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: run-llama/liteparse — let's break it down. 🔗 https://github.com/run-llama/liteparse 📝 A fast, helpful, and open-source document parser ────────────────────────────── LiteParse is a fast and lightweight, open-source PDF parsing tool that delivers high-quality spatial text parsing with bounding boxes. It runs locally on your machine, without relying on proprietary features or cloud dependencies. Key features of LiteParse include fast text parsing using PDFium, a flexible OCR system with built-in Tesseract and support for HTTP servers, screenshot generation, and multiple output formats like JSON and text. It also supports multi-language use from Rust, Node.js/TypeScript, Python, or the browser (WASM) and is multi-platform, compatible with Linux, macOS, and Windows. To install LiteParse, you can use your preferred package manager. For example, you can install it via npm for Node.js/TypeScript, pip for Python, or cargo for Rust. The CLI usage is straightforward. You can parse files using the lit parse command, generate screenshots with lit screenshot, and perform batch parsing with lit batch-parse. Technical highlights include automatic conversion of various document formats to PDF before parsing, support for office documents via LibreOffice, and image formats via ImageMagick. Audience: LiteParse is suitable for developers and users who need fast and accurate PDF parsing capabilities, especially those working with large volumes of documents or requiring precise text positioning information. In summary, LiteParse is a powerful, user-friendly tool that provides fast and accurate PDF parsing, making it an excellent choice for anyone looking to extract valuable information from their documents - Parse your documents, unleash the power of your data. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 cursor/plugins caught my eye on GitHub Trending today. 🔗 https://github.com/cursor/plugins 📝 Cursor plugin specification and official plugins ────────────────────────────── The Cursor plugins repository offers a collection of official plugins for various developer tools, frameworks, and SaaS products. Each plugin is a standalone directory with its own manifest, making it easy to manage and maintain. Key features include continual learning for incremental memory updates, thermos for deep security audits, and create-plugin for scaffolding new plugins. To use these plugins, simply navigate to the desired plugin directory and follow the instructions in the README.md file. From a technical standpoint, the repository uses a marketplace.json file to list all available plugins, and each plugin has its own plugin.json manifest. These plugins are perfect for developers and dev teams looking to streamline their workflow and improve productivity. In short, the Cursor plugins repository is a game-changer for development teams - it's like having a superpower in your coding toolkit. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: Leonxlnx/taste-skill — let's break it down. 🔗 https://github.com/Leonxlnx/taste-skill 📝 Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop ────────────────────────────── Taste Skill is an innovative GitHub repository designed to enhance the capabilities of AI agents in building premium frontends. The repo offers a range of portable agent skills that focus on improving layout, typography, motion, and spacing, resulting in more sophisticated and polished UIs. Key features include adjustable dials for design variance, motion intensity, and visual density, allowing for customized outputs. The skills are framework-agnostic and compatible with major coding agents like Codex, Cursor, and Claude Code. To get started, simply install the desired skill using npx skills add https://github.com/Leonxlnx/taste-skill, then use the installed skill in your agent conversations. For image-generation skills, pair them with ChatGPT Images or similar generators to produce design images. The repo is suitable for developers and designers looking to elevate their frontend builds with AI-driven design skills. With its unique approach to anti-slop design and extensive research backing, Taste Skill is a valuable tool for anyone seeking to create high-end interfaces. In a nutshell, Taste Skill is a game-changer for AI-powered frontend development - revolutionizing the way we design and build premium UIs, one skill at a time. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🎯 anthropics/claude-code landed on trending. Worth a proper look. 🔗 https://github.com/anthropics/claude-code 📝 Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands. ────────────────────────────── Claude Code is a terminal-based coding tool that uses natural language commands to help you code faster by executing routine tasks and handling git workflows. Key features include understanding your codebase and explaining complex code. To get started, install it via the recommended methods, then navigate to your project directory and run claude. The tool also includes plugins that extend its functionality with custom commands and agents. For technical users, the code is available on GitHub, and the community can be reached on Discord for feedback and discussion. Claude Code is suitable for developers of all levels looking to streamline their coding process. One-liner takeaway: With Claude Code, you can claude your way to faster coding. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ twentyhq/twenty is making waves. Here's the full picture. 🔗 https://github.com/twentyhq/twenty 📝 The open alternative to Salesforce, designed for AI. ────────────────────────────── The Twenty GitHub repository is an open-source CRM that provides building blocks for a custom customer relationship management system. Its key features include objects, views, workflows, and agents that can be extended as code. With Twenty, you can create a custom CRM that meets complex business needs and evolves quickly. To get started, you can either sign up for a cloud workspace, build an app using the Twenty CLI, or self-host it on your own infrastructure. The npx create-twenty-app my-app command scaffolds a new app, and you can define objects, fields, and views as code using the twenty-sdk/define module. The technical stack includes TypeScript, Nx, NestJS, PostgreSQL, Redis, and React. The project is actively maintained, and the community is encouraged to contribute through discussions, feature requests, and code contributions. The best way to summarize Twenty is: Build your custom CRM, ship it like code, and version it like the rest of your stack - with Twenty, the possibilities are endless! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

⚡ EveryInc/compound-engineering-plugin is making waves. Here's the full picture. 🔗 https://github.com/EveryInc/compound-engineering-plugin 📝 Official Compound Engineering plugin for Claude Code, Codex, Cursor, and more ────────────────────────────── The Compound Engineering plugin is designed to make each unit of engineering work easier than the last. It inverts the traditional development approach by focusing on planning, review, and codifying knowledge to create a compound effect. The plugin provides a range of skills and agents to support this approach, including /ce-brainstorm, /ce-plan, and /ce-code-review. To get started, users can install the plugin using various methods, including Claude Code, Cursor, Codex, Copilot, Factory Droid, Qwen Code, and others. The plugin is designed to be flexible and adaptable, with a range of features and tools to support different workflows and use cases. Key features of the plugin include: * /ce-strategy for creating and maintaining a product's target problem, approach, persona, and key metrics * /ce-ideate for generating and critically evaluating ideas * /ce-brainstorm for interactive Q&A to think through a feature or problem * /ce-plan for turning feature ideas into detailed implementation plans The plugin also includes a range of technical highlights, including: * Support for multiple installation methods * A range of skills and agents to support different workflows and use cases * A flexible and adaptable architecture to support customization and extension The Compound Engineering plugin is designed for a range of users, including developers, engineers, and project managers. It is particularly suited to teams and organizations that want to improve their engineering workflow and create a more efficient and effective development process. One-liner takeaway: Compound Engineering plugin helps teams create a more efficient and effective development process by focusing on planning, review, and codifying knowledge to create a compound effect. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe