Rankeo Chunk Test
Also known as: Test de Chunk Rankeo
The Rankeo Chunk Test is a proprietary 3-question method for verifying whether a piece of content is properly chunkable by Large Language Models (LLMs) and, consequently, extractable in AI-generated responses. It is a rapid diagnostic tool that takes 5 minutes per article and reveals structural weaknesses that would otherwise remain invisible.
Definition
LLMs do not read articles the way humans do. They break content into chunks of approximately 300-500 tokens, embed those chunks into vector space, and retrieve them at query time. If your content is not structured to survive this chunking process, your best insights get fragmented across chunks that lose their meaning individually. You become invisible to the retrieval mechanism even if your content is brilliant.
The Rankeo Chunk Test addresses this by asking three questions about any chunk-sized block of your content: (1) Does it contain a self-sufficient claim? (2) Does it include contextual entity markers (who, what, where)? (3) Is it extractable as a standalone paragraph without losing meaning? A content block that answers "yes" to all three is chunk-compliant.
How It Works
The test is applied to each section of your content, one at a time. You copy the section into a text editor and read it without the surrounding context — imagine it was the only thing an LLM retrieved.
Question 1 — Self-sufficient claim. Does this paragraph make a specific, verifiable claim on its own? If the paragraph says "this is a great approach because of the reasons mentioned above", it fails — the claim depends on prior context the LLM may not retrieve. If it says "The Rankeo Chunk Test improves chunk-retrieval performance by 34% according to our 501-site benchmark", it passes.
Question 2 — Contextual entity markers. Can the reader identify the who/what/where without scrolling? If your paragraph says "we found that...", it fails — who is "we"? Where was this found? If it says "Rankeo's 2026 benchmark of 501 sites found that...", it passes.
Question 3 — Extractability. If the LLM retrieves only this paragraph, does the user receive value? If the paragraph is a transition ("Now let's move to the next point"), it fails. If it is a complete idea with its own conclusion, it passes.
Practical Example
Original paragraph (fails): "As we saw earlier, this method is effective. Many of our users report significant improvements. We recommend trying it."
Rewritten paragraph (passes): "The Rankeo Chunk Test, applied to 47 consultant client sites in Q1 2026, produced an average 34% improvement in AI citation retrieval rates within 60 days. Users who restructured 3 articles using the test framework saw their Citation Velocity Score double, from 1.1x to 2.2x."
The rewritten version is self-sufficient, entity-marked, and extractable. An LLM retrieving only this chunk delivers actionable information to the user.