AI Agent Skills

👩🏻‍🍳 A collection of example notebooks using Haystack

Design n8n AI agents the right way. Use when building or editing any @n8n/n8n-nodes-langchain.* AI node — an AI Agent, LLM chain, Text Classifier, or Information Extract…

Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF…

🧠 AI-powered Personalized Exam System: Integrating OpenPangu LLM, Knowledge Graph RAG, and BKT algorithm for adaptive question generation and recommendation. 基于LLM与知识图谱…

Summarize and query from a lot of heterogeneous documents. Any LLM provider, any filetype, advanced RAG, advanced summaries, scriptable, etc

Text-To-Speech, RAG, and LLMs. All local!

[ICLR 2026] LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora

Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.

A comprehensive guide to building RAG-based LLM applications for production.

NextPlaid, ColGREP: Multi-vector search, from database to coding agents.

制作懂人情世故的大语言模型 | 涵盖提示词工程、RAG、Agent、LLM微调教程

Fast and efficient unstructured data extraction. Written in Rust with bindings for many languages.

软件开发工程师与数据科学家在构建RAG系统时，当需处理PDF/Word/Excel等多格式复杂文档，用此技能可自动触发三级解析降级，一键输出高置信度结构化Markdown与元数据，免去繁琐清洗，直接夯实企业知识库数据底座！

The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

A filesystem designed for agents, with SOTA retrieval, automatic memory profiles, sync engine. Drop any file type (pdf, images, videos), and grep through them.

Context drive for your AI agents