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chunking-strategies

Split documents for retrieval effectively — fixed, semantic, structural, and hierarchical chunking with overlap tuning. Use when RAG retrieval quality depends on how documents are divided.

skills/chunking-strategies/SKILL.md

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# Chunking Strategies

Chunking decides what the retriever can find: too large and the signal drowns; too small and 
context is lost; split in the wrong place and meaning breaks. It's the highest-leverage decision in 
most RAG pipelines — and the most under-tuned.

## Overview

Strategies range from naive (fixed token windows) to structure-aware (split on headings, 
paragraphs, tables) to semantic (split where meaning shifts) to hierarchical (small chunks with 
parent context). Overlap preserves boundary context. The right choice depends on content type — 
prose, tables, code, and transcripts chunk differently — and must be validated by inspecting 
actual chunks and measuring retrieval, not by theory.