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RAG Pipeline Architect

Agent skill
1 skill
READMEOverview ↓

Design and architect RAG (Retrieval-Augmented Generation) pipelines. Covers vector DB selection, chunking strategies, hybrid retrieval (vector + knowledge graph), semantic caching, ingestion pipeline design, embedding model selection, and production deployment patterns. Triggers on: RAG, retrieval augmented generation, vector database, embeddings, chunking, FAISS, Qdrant, Milvus, pgvector, Weaviate, Pinecone, knowledge graph, Neo4j, semantic search, document Q&A, ingestion pipeline, reranking, hybrid search, or any question about building a RAG system.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryEngineeringStars0

About this skill

Design and architect RAG (Retrieval-Augmented Generation) pipelines. Covers vector DB selection, chunking strategies, hybrid retrieval (vector + knowledge graph), semantic caching, ingestion pipeline design, embedding model selection, and production deployment patterns. Triggers on: RAG, retrieval augmented generation, vector database, embeddings, chunking, FAISS, Qdrant, Milvus, pgvector, Weaviate, Pinecone, knowledge graph, Neo4j, semantic search, document Q&A, ingestion pipeline, reranking, hybrid search, or any question about building a RAG system.

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.

Installation guide →

Review, license & listing details
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This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

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Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.

0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: 591f3f32ea83326835984ec52d587af5a4af51e1f043db297a3a88709e9fd46b

About scan coverage and limitations
Original listing metadata

Original name

rag-pipeline-architect

Original description

Design and architect RAG (Retrieval-Augmented Generation) pipelines. Covers vector DB selection, chunking strategies, hybrid retrieval (vector + knowledge graph), semantic caching, ingestion pipeline design, embedding model selection, and production deployment patterns. Triggers on: RAG, retrieval augmented generation, vector database, embeddings, chunking, FAISS, Qdrant, Milvus, pgvector, Weaviate, Pinecone, knowledge graph, Neo4j, semantic search, document Q&A, ingestion pipeline, reranking, hybrid search, or any question about building a RAG system.

About this listing

Category
Engineering
Reported license
Not specified
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
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