Run a whole-page extractability audit
Paste the rendered text of a page and ask Claude to identify every passage that would fail if lifted out of context - pronouns without referents, answers split across sections, claims without numbers. Its long context means it evaluates the page as one document rather than a sample.
Do side-by-side chunk comparisons
Paste your page and the page currently cited for the query, and ask which passages a retrieval system would prefer and why. This is the fastest way to see that the winner is usually shorter, more specific, and better labelled - not better written.
Test how Claude describes you
With web search on, run your buying-intent prompt set and log mentions and cited URLs. Claude tends to cite fewer sources per answer than other assistants, which makes its citations a stricter test of source quality.
Draft structured answers under constraint
Give explicit constraints - 55 words, no adjectives, one statistic, must stand alone - and Claude will hold them across many sections at once. That consistency matters when you are rewriting forty answer blocks in a sitting.
Generate and validate schema
Ask for FAQPage or HowTo JSON-LD that matches the visible text exactly, then validate it. Mismatch between markup and visible content is a common cause of ignored markup, and a long-context model can check both at once.
Keep the crawler question separate
Appearing in Claude's search answers requires allowing its search crawler. Decide that independently of whether you allow training crawlers; the two use different user agents and have different consequences.