Stars
The official Lark/Feishu CLI tool, maintained by the larksuite team — built for humans and AI Agents. Covers core business domains including Messenger, Docs, Base, Sheets, Calendar, Mail, Tasks, Me…
Skills for Real Engineers. Straight from my .claude directory.
OmX - Oh My codeX: Your codex is not alone. Add hooks, agent teams, HUDs, and so much more.
Documentation for n8n, a fair-code licensed automation tool with a free community edition and powerful enterprise options. Build AI functionality into your workflows.
AG-UI: the Agent-User Interaction Protocol. Bring Agents into Frontend Applications.
A collection of DESIGN.md files analysis by popular brand design systems. Drop one into your project and let coding agents generate a matching UI.
List of awesome RSS channels related to startup, science and technology.
Awesome RSS feeds - A curated list of RSS feeds (and OPML files) used in Recommended Feeds and local news sections of Plenary - an RSS reader, article downloader and a podcast player app for android
⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构…
TradingAgents: Multi-Agents LLM Financial Trading Framework
Chrome DevTools for coding agents
A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes…
"CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub: https://clianything.cc/
Reverse Engineering of LEGO Mario, Luigi, and Peach
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
NeuraLint: Automatic Fault Detection for Deep Learning Programs Using Graph Transformations
Deep Reinforcement Learning Method Implemented In The Groove Graph Transformation Tool For Model Checking
Exploring techniques for estimating safety of machine learning classifiers
📚 Freely available programming books
Paper list of multi-agent reinforcement learning (MARL)
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes