React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
Skill-Verzeichnis
Wiederverwendbare Skills für AI Agents entdecken.
Jede Empfehlung bleibt mit ihrem Repository, Audit und Installationspfad nachvollziehbar.
Suchergebnisse: cross-modal-retrieval
Englisches VerzeichnisRAGFlow 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.
The best free and open-source automated time tracker. Cross-platform, extensible, privacy-focused.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
Cross-platform, customizable ML solutions for live and streaming media.
A modular graph-based Retrieval-Augmented Generation (RAG) system
Cross-CLI skill for Obsidian: turn your vault into a living AI-first second brain across Claude Code, Codex, Gemini, and OpenCode. 43 commands - now with /obsidian-architect to document your codebase, key-less web research, Google Calendar, and self-rewriting notes.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
KeePassXC is a cross-platform community-driven port of the Windows application “KeePass Password Safe”.
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
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.