Knowledge Base
Feature

Suggestions

Every scan turns what it finds into a prioritised fix list — technical, on-page, off-page, and AI-visibility actions with the impact explained.

Where suggestions come from

Suggestions aren't a static checklist — they're regenerated from your data on each analysis run. Issues detected across your scans and crawls (missing FAQ or schema, blocked AI bots, thin content, missing author bios, and more) become concrete suggestions, and stale ones are cleared each run so the list reflects your site as it is now.

The queue

Suggestions are grouped under tabs with live counts — All / Technical / On-Page / Off-Page / AI Visibility — and sorted by severity, critical first. Expand any card for the full detail.

Anatomy of a suggestion

  • What was detected — the specific issue, tied to your site.
  • Why it matters for AI — the impact on how AI systems read and cite you, with an estimated citation effect.
  • The recommended fix — what to actually do, with an effort level so you can plan the work.

Working the list

Mark suggestions resolved as you fix them. Because the list regenerates from fresh data, a genuinely fixed issue stays gone — and one that wasn't fully fixed comes back, which is exactly what you want from a fix list.

Critical first, then quick wins. Work the severity order for impact, but keep an eye on low-effort items — a five-minute schema fix can be worth more than it looks.