Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
A collection of practical, installable AI agent skills for disk cleanup, AI news retrieval, and project management, following the Agent Skills standard.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
A comprehensive collection of ready-to-use scientific and research skills for AI agents.
A modular graph-based Retrieval-Augmented Generation (RAG) system
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
A Codex skill for generating minimal zine-style editorial poster prompts and images.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
A collection of practical, installable AI agent skills for disk cleanup, AI news retrieval, and project management, following the Agent Skills standard.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
A comprehensive collection of ready-to-use scientific and research skills for AI agents.
A modular graph-based Retrieval-Augmented Generation (RAG) system
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
A Codex skill for generating minimal zine-style editorial poster prompts and images.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
A collection of practical, installable AI agent skills for disk cleanup, AI news retrieval, and project management, following the Agent Skills standard.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
A comprehensive collection of ready-to-use scientific and research skills for AI agents.
A modular graph-based Retrieval-Augmented Generation (RAG) system
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
A Codex skill for generating minimal zine-style editorial poster prompts and images.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
A collection of practical, installable AI agent skills for disk cleanup, AI news retrieval, and project management, following the Agent Skills standard.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
A comprehensive collection of ready-to-use scientific and research skills for AI agents.
A modular graph-based Retrieval-Augmented Generation (RAG) system
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
A Codex skill for generating minimal zine-style editorial poster prompts and images.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.