LangChain · Vector databases

Sets up FAISS for fast nearest-neighbor search over large collections of dense vectors, choosing between Flat, IVF, HNSW and product quantization indexes.

Orchestra-Research/AI-Research-SKILLs

Shows how to use Pinecone, a managed vector database, for production RAG, semantic search and recommendations: indexes, upserts, queries, filters and namespaces.

Orchestra-Research/AI-Research-SKILLs

Framework for building LLM-powered applications with agents, chains, and RAG.

Orchestra-Research/AI-Research-SKILLs

Designs retrieval-augmented generation systems: document chunking, embeddings, vector store setup, hybrid search, reranking and retrieval evaluation, with checks at each step.

Jeffallan/claude-skills

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system.

langchain-ai/langchain-skills

Operating-system distillation of LlamaIndex — the leading RAG / document-agent framework.

agentsope/SkillAlchemy

Security-first SOP for multi-tenant RAG systems. An agent skill from agentsope/SkillAlchemy.

agentsope/SkillAlchemy

Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+).

neo4j-contrib/neo4j-skills

Build and query vector stores with LangChain 1.0 without getting burned by flipped score semantics, embedding-dim mismatches, reranker quirks, and chunk-splitter bugs.

jeremylongshore/tons-of-skills-marketplace