AI Agent Skills

:package::rocket: Fully automated version management and package publishing

Compose enterprise LLM agents and plugins

Superfast AI decision making and intelligent processing of multi-modal data.

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.

Semantica 🧠 — AI-native knowledge graph intelligence framework for semantic retrieval, ontology reasoning, context graphs, and explainable AI systems.

A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex), backed by Markdown and Milvus.

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search.…

Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.

Semantic search and document parsing tools for the command line

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 26 languages via tree-sitter. Built for coding agents.

The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure

📊 Cube Core is open-source semantic layer for AI, BI and embedded analytics

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 L…

Universal memory layer for AI Agents

OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched