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Chunk & Token Visualizer

Paste a document and see exactly how it splits for embeddings — chunk size, overlap, token estimate per chunk, and what your retriever actually indexes. Tokens are estimated (~4 chars/token); use it to reason about retrieval, not for exact billing.

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chunks
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est. tokens
$0.0000
embed cost (3-small)
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avg tokens/chunk
Tuning chunking by hand gets old fast. CiteKit ships a deterministic ingest (chunk → embed → upsert) and an eval harness so you can measure whether your chunking actually improves retrieval — not just guess.
Get CiteKit — $129
Why chunking matters

Retrieval is only as good as your chunks.

Too big, and a chunk mixes topics — the embedding is muddy and retrieval pulls the wrong thing. Too small, and you lose the context that makes an answer correct. Overlap keeps a sentence that straddles a boundary findable from both sides. There's no universal best — measure it on your own questions. That's the whole point of an eval set.