couchbase-ai-applicationslisted

Design and build AI-powered applications on Couchbase, including RAG pipelines, vector search architecture, embedding strategies, and AI agent data patterns. Use whenever the user asks about RAG, retrieval-augmented generation, vector search for AI, Hyperscale Vector Index (HVI), Composite Vector Index (CVI), Search Vector Index (SVI), embedding pipelines, semantic search, AI agent memory, grounding LLMs with Couchbase, agentic data patterns, billion-scale vector search, multi-vector search, AI application architecture, or 'how do I build an AI app with Couchbase.' Distinct from couchbase-fts (which covers FTS index mechanics and query syntax) — this skill is about end-to-end AI application design: the data model, embedding pipeline, index type selection, retrieval strategy, and integration with LLM frameworks. Use proactively when the user is building AI features or has a use case involving language models, embeddings, or semantic retrieval.
celticht32/Couchbase-Skills-for-Claude.ai · ★ 1 · AI & Automation · score 75

Install: claude install-skill celticht32/Couchbase-Skills-for-Claude.ai

# Couchbase AI Applications A skill for *designing AI-powered applications* on Couchbase — RAG pipelines, vector search architecture, embedding strategies, and agent memory patterns. Covers the full stack from document design through embedding generation, index selection, retrieval, and LLM integration. Distinct from: - `couchbase-fts` — FTS index mechanics and query syntax (the lower-level how); this skill is about the application-level what and why - `couchbase-data-modeling` — general document design; this skill covers AI-specific document patterns - `couchbase-app-integration` — SDK patterns; this skill covers AI framework integration If the conversation is "I'm building an AI feature / RAG pipeline / agent," this is the right skill. ## When this skill applies - "How do I build a RAG pipeline with Couchbase?" - "Which vector index type should I use — HVI, CVI, or SVI?" - "How do I store and search embeddings at scale?" - "How do I combine vector search with keyword/metadata filters?" - "How do I use Couchbase as memory for an AI agent?" - "What's the difference between Hyperscale and Composite vector indexes?" - "How do I integrate Couchbase with LangChain / LlamaIndex?" - "How do I build a billion-scale vector search?" - "How do I evaluate retrieval quality in my RAG pipeline?" ## Pick the right reference | Question | Read | |---|---| | "Which of the three vector index types should I use?" | `references/vector-index-types.md` | | "How do I design my documents and