Stars
天工开物 — AI Agent 朝廷框架。三省六部制 × Terminal AI Agent。
Run OpenClaw more securely inside NVIDIA OpenShell with managed inference
📜 Sun Tzu's Art of War applied to AI agent organization and task orchestration — 13 chapters mapped to practical agent patterns
A native communication protocol made by AI agents, for AI agents.
LeoLin990405 / civagent
Forked from wanikua/danghuangshang🎮 CivAgent (AI 文明) — 57 historical governance systems mapped to AI multi-agent orchestration patterns. Choose your civilization, command your AI team. 人类5000年治国智慧 × AI多Agent协作
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
A local LLM router that intelligently dispatches AI requests to the right model — saving cost without sacrificing quality.
A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic
The cutest instant messenger in the [matrix]
🧠 20 human thinking frameworks as Claude Code custom commands — Critical Thinking, First Principles, Red Team, Bayesian, and more
One command to uninstall ALL Claw-family AI agents. Zero residue. 一键卸载所有 Claw 家族 AI Agent，无残留。
Your AI executive team on Discord. 7 specialized agents — Engineering, Finance, Marketing, DevOps, Legal, Management, Chief of Staff. One-click setup on any free-tier server. Built on Clawdbot.
A python library for self-supervised learning on images.
An Open-Ended Embodied Agent with Large Language Models
wanikua / OpenBB
Forked from OpenBB-finance/OpenBBInvestment Research for Everyone, Everywhere.
From Thoughts to Well-Crafted Jupyter Notebook at Record-Speed
✯ 可直连访问的电视/广播图标库与相关工具项目 ✯ 🔕 永久免费 直连访问 完整开源 不断完善的台标 支持IPv4/IPv6双栈访问 🔕
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
PyTorch入门教程，在线阅读地址：https://datawhalechina.github.io/thorough-pytorch/
Summaries / Cheat Sheets created at ETH Zurich BsC Computer Science & MsC Data Science
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。