Retrievability Score
Get one score per page plus an individual 0-100 score for every chunk, so you can see exactly where retrieval breaks down.
Passage & Chunk Optimization Checker for AI Retrieval
TL;DR: Passage & Chunk Optimization Checker checks segment a page into retrieval chunks and score each for ai extractability. so you can confirm the current issue, understand when it matters, and move directly into the next fix without leaving the browser.
See how an answer engine carves your page into chunks, and which ones fail in isolation.
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Heading-section and paragraph chunk segmentation Pronoun-orphan opening detection Chunk length and density scoring Direct-claim lead-sentence analysis Worst-offenders ranking with fix guidance
What does Passage & Chunk Optimization Checker do?
Passage & Chunk Optimization Checker splits a page the way retrieval systems do, then scores each segment for whether it can stand alone as a quotable answer. It walks the heading and paragraph structure with Cheerio, groups prose into retrieval chunks, and flags the patterns that break extraction.
Why chunks matter for AI SEO: ChatGPT, Perplexity, and Google's AI Overviews rarely quote a whole page. They embed and retrieve individual passages, then surface the one that best answers a query. A chunk that loses meaning out of context is a chunk that never gets cited, no matter how strong the surrounding article is.
Pronoun-orphan detection: A passage that opens with "It does this by..." or "They are the reason..." has no antecedent once it is pulled from the page. We catch these orphaned openings so you can restate the subject and make the chunk self-sufficient.
Length and lead-claim scoring: Chunks that are too long bury the answer; chunks that are too short cannot carry one. We also check whether each passage leads with a direct claim instead of a hedge or a scene-setting clause, the single biggest driver of clean extraction.
Editorial QA and refresh: Run a draft before publishing to find the passages that will not survive retrieval, then rerun after edits to confirm your worst offenders now stand on their own.
When should you use Passage & Chunk Optimization Checker?
Passage & Chunk Optimization Checker is most useful when you need a direct answer on a live URL or draft before you change templates, ship content, or rerun a wider audit.
So verwenden Sie dieses Tool
- 1 Enter a page URL.
- 2 Run the chunk segmentation and scoring.
- 3 Review per-chunk scores and the worst offenders.
- 4 Rewrite weak passages and rerun to confirm the lift.
What should you do next?
After tightening chunks, validate answer extractability and citation readiness across the page. Then move to the related checks below to confirm the fix on the live canonical page.
Was Sie bekommen
Worst Offenders First
Surface the lowest-scoring passages at the top with concrete reasons, so you fix what moves the needle before anything else.
Self-Containment Checks
Flag pronoun orphans, missing lead claims, and length problems that stop a chunk from standing alone when an AI quotes it.
Frequently Asked Questions
Antworten zu Passage & Chunk Optimization Checker
A retrieval chunk is the slice of your page an AI system embeds and quotes in isolation, usually a heading section or paragraph group. Answer engines almost never cite a full article. They index and rank individual passages, then surface the best one for a query. If a chunk only makes sense in the context of the paragraph above it, it gets skipped, so optimizing at the chunk level directly affects whether you get cited.
A pronoun-orphan opening is a passage that starts with a back-reference like "It," "This," or "They" that has no antecedent inside the chunk itself. When the passage is pulled out for retrieval, the reader and the model have no idea what "it" refers to. The fix is to restate the subject in the first sentence so the chunk is self-sufficient, for example replacing "It improves rankings" with "Structured data improves rankings."
Aim for a focused passage of roughly 25 to 220 words that carries one complete idea. Chunks under about 25 words rarely contain a full, quotable answer, while chunks over 220 words tend to bundle several ideas and dilute the one a query is asking about. The checker flags both extremes so you can split overloaded passages and flesh out thin ones.
Leading with a direct claim means the first sentence of a chunk asserts the answer instead of warming up to it. Passages that open with connectives, hedges, or a long subordinate clause bury the point a model is trying to extract. A chunk that opens with the conclusion, then supports it, is far more likely to be quoted verbatim in an AI Overview or chatbot answer.