Build Your Own OpenClaw
🧠A progressive AI Agent building tutorial covering 18 steps to implement a lightweight OpenClaw (pickle-bot) from scratch, featuring tool calling, multi-agent collaboration, and production-grade capabilities.
A progressive AI Agent building tutorial covering 18 steps to implement a lightweight OpenClaw (pickle-bot) from scratch, featuring tool calling, multi-agent collaboration, and production-grade capabilities.
A minimal, learning-oriented reimplementation of the OpenClaw core architecture, demonstrating system-level AI Agent design including dual-loop Agent Loop, EventStream, Session persistence, three-tier context management, and WebSocket RPC gateway.
An AI Agent-driven automated experiment framework that points at any code repo, autonomously analyzes, designs, runs experiments, and keeps improvements that work
An all-in-one AI ecosystem browser in the terminal — explore models, benchmarks, coding agents, and provider status via TUI/CLI
A modular Python toolkit developed by the University of Innsbruck that integrates information retrieval, re-ranking, and RAG generation, featuring 40+ pre-processed datasets and single-line pipeline construction.
A systematic skill library for AI Agent context management, covering fundamentals, architectural patterns, operational optimization, and evaluation systems. Compatible with Claude Code, Cursor, and other platforms. Distinguished from prompt engineering by its holistic approach to curating all information entering the model's attention budget.
A continuously updated repository systematically organizing 106 research papers on Large Language Model-based agents for Software Engineering, categorized from both Software Engineering and agent architecture perspectives.
A benchmark for evaluating the code generation capabilities of large language models, featuring 1,140 software-engineering-oriented programming tasks with two modes (Complete and Instruct) to test models on complex instructions and diverse function call scenarios.
An interactive debugging tool designed for deep learning research that enables real-time visualization, inspection, and analysis of neural network behavior directly within Jupyter notebooks.
An open-source framework designed to build intelligent search and research agents with capabilities for deep web search, content extraction, and comprehensive answer generation.
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