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# Chunking Strategies Comparison ## Executive Summary Document chunking is the foundation of effective RAG systems. This analysis compares five primary chunking strategies across key metrics including semantic coherence, boundary quality, processing speed, and implementation complexity. ## Strategies Analyzed ### 1. Fixed-Size Chunking **Approach**: Split documents into chunks of predetermined size (characters/tokens) with optional overlap. **Variants**: - Character-based: 512, 1024, 2048
How to Use
Recommended: Install to project (local)
mkdir -p .claude/skills
curl -o .claude/skills/chunking_strategies_comparison.md \
https://raw.githubusercontent.com/alirezarezvani/claude-skills/main/engineering/rag-architect/references/chunking_strategies_comparison.mdSkill is scoped to this project only. Add .claude/skills/ to your .gitignoreif you don't want to commit it.
Alternative: Clone full repo
git clone https://github.com/alirezarezvani/claude-skillsThen reference at engineering/rag-architect/references/chunking_strategies_comparison.md
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