chunking-strategieslisted

# Chunking strategies Chunking decides what retrieval can ever return. A chunk that splits a definition from its example, or a table from its header, cannot be rescued by a better embedding model or a smarter reranker. Most RAG quality problems are chunking problems. ## Method 1. **Split on structure before size.** Headings, sections, and paragraphs are meaning boundaries the author already provided, and respecting them beats any fixed character count. 2. **Size to the question, not to the model's limit.** Chunks large enough to contain a complete answer and small enough that most of the chunk is relevant, which is usually far below the context window. 3. **Overlap modestly at boundaries.** A small overlap prevents an answer that straddles a split from being lost, at the cost of some duplication in results. 4. **Carry context into the chunk.** Document title, section heading, and date prepended to the text, since a retrieved chunk arrives without its surroundings and must stand alone. 5. **Treat tables, code, and lists as units.** Splitting them produces fragments that are worse than useless because they look authoritative and are incomplete (see document-parsing). 6. **Keep a link back to the source location.** Every chunk needs enough provenance to cite and to let a user open the original (see citation-grounding). 7. **Evaluate chunking as a variable.** Re-index with different strategies and measure retrieval quality, because intuit