Learning Resources ListingsLearning Resources

Skrl

Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments

Building A Coding Agent From Scratch Course

Learn harness engineering by building Claude Code from scratch. Free, open-source course: 8 articles, 6 videos, 1 codebase.

GPTSwarm

🐝 The First Self-Improving agents with RL / Prompting Optimization

Learnpython

Python Resources for Everyone

Agent Purge

One persona, many coding agents. Replace or inject system prompts across codex, claude, opencode, grok, omp, hermes, pi, zcode - with a local web console.

How To Vibecoding

Vibecoding 系列教程：从环境搭建到多智能体协作，涵盖 MCP、Skills、Agent 分工治理

Most Capable Agent System Prompt

A copy-paste system prompt that has your coding agent (Claude Code, Codex, Cursor) build a self-improving agent system for any computer work.

MCP Nixos

MCP-NixOS - Model Context Protocol Server for NixOS resources

Doc To Lora

Hypernetworks that update LLMs to remember factual information

MCP Client For Ollama

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

Typescript Style Guide

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Dbt Agent Skills

A curated collection of Agent Skills for working with dbt, to help AI agents understand and execute dbt workflows more effectively.

Langgraph Course

Hands-on LangGraph course repo for building production-grade LLM agents with Agentic RAG, ReAct, and reflection workflows.

MCP Nest

A NestJS module to effortlessly create Model Context Protocol (MCP) servers for exposing AI tools, resources, and prompts.

Langchain1 0 Langgraph1 0 Learning

这是一个 LangChain 1.0 和 LangGraph 1.0 的学习仓库，学习如何进行agent开发，涵盖从基础概念到实战项目的完整学习路径。

BenchMARL

BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically grounded in its two core tenets: reproducibility and standardization.

Open AgentRL

RLAnything (ICML 2026) & AutoTool (ICML 2026), DemyAgent: Open-Source RL for LLMs and Agentic Scenarios

Agent Learning

A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch

NWave

AI agents that guide you from idea to working code, with you in control at every step.

VectorizedMultiAgentSimulator

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

MCP Sequentialthinking Tools

🧠 An adaptation of the MCP Sequential Thinking Server to guide tool usage. This server provides recommendations for which MCP tools would be most effective at each stage.

Multimodal Agents Course

An MCP Multimodal AI Agent with eyes and ears!

Deerflow Book

本书围绕 DeerFlow 2.0，从理论到源码，系统讲解如何进行二次开发。(精校)

Smart Illustrator

AI-powered article illustrations with intelligent position detection and cover learning system. Claude Code Skill.