| name | rag-indexer |
| description | Design document ingestion and indexing workflows for Azure AI Search, including chunking, metadata strategy, and incremental reindexing guidance. |
RAG Indexer
Use this skill to define and improve indexing pipelines for RAG on Azure AI Search.
Use for
- Source inventory and ingestion sequencing
- Chunking and overlap strategy selection
- Metadata schema design for filters and citations
- Hybrid retrieval baseline (keyword + vector + semantic ranker)
- Reindexing strategy for changed documents
Do not use for
- End-user chat UX implementation
- Azure subscription governance and policy enforcement
Output contract
Provide:
- Ingestion workflow by source type
- Chunking and embedding settings
- Index schema proposal
- Retrieval tuning checklist
- Verification queries and expected outcomes