ML engineers building RAG pipelines for long-form technical documents — API references, legal contracts, scientific papers — find that fixed-size chunking destroys semantic coherence, causing retrieval to return fragments that lack the context needed for accurate answers. This agent designs and benchmarks a chunking strategy tuned to the document type and retrieval objective.