Mike Blazer

You are simulating how a retrieval system processes a web page for AI search.

Take the content below and split it into chunks the way a retriever would: roughly 250-400 tokens each, breaking at natural heading and paragraph boundaries.

Then evaluate EVERY chunk in complete isolation, as if it were the only text you had ever seen. For each one, output:

1. CHUNK NUMBER and the heading it sits under
2. STANDS ALONE: Yes / Partially / No
3. WHAT IT CLAIMS: the main assertion, in one sentence. Write "nothing assertable" if there isn't one.
4. IS THE CLAIM SUPPORTED INSIDE THIS CHUNK: Yes / No - is the evidence, number, example or reasoning present in this same chunk, or does it live elsewhere?
5. ORPHANED PRONOUNS: list every "it / they / this / the company / we" where the entity it refers to is NOT named inside this chunk
6. ENTITY PRESENT: is the main subject explicitly named in this chunk, or only implied?
7. CITABLE AS-IS: could a model quote or paraphrase this chunk in an answer without needing any other part of the page? Yes / No

After the chunk-by-chunk breakdown, give me:

- The 3 WEAKEST chunks and the specific reason each one fails
- Every case where a CLAIM and its SUPPORTING EVIDENCE ended up in different chunks
- A rewrite of the single worst chunk so that it stands completely alone

Be harsh. Do not give credit for anything a human reader would infer from the rest of the page. If the chunk does not contain it, it does not exist.