Top Fixes per pillar

Prioritized recommendations from the audit.

Last updated: 2026-05-05

Top Fixes per pillar

Every audit ends with a Top Fixes panel — the smallest set of changes that would move your score the most. The list is ordered by expected score impact (not difficulty), so the first item is always the highest-leverage fix.

How fixes are ranked

Each detected issue carries:

Severity (Critical / High / Medium / Low) — how much it depresses the pillar score
Pillar weight — Discoverability fixes outrank Authority fixes when both are equally severe, because Discoverability gates everything else
Effort estimate — purely informational; not used in ranking

The ranking is impact-first because most users have limited engineering time and want to know "if I fix one thing, what?".

Fix priority reference

Pillar	Ranking priority	Typical highest-impact fix	Usual effort
Discoverability	Highest — gates everything else	Remove inherited robots.txt Disallow rules for AI agents	Quick
Discoverability	Highest	Publish a root-level llms.txt	About 5 minutes
Authority	Medium	Add Organization JSON-LD with logo, sameAs and contact	Quick
Authority	Medium	Wrap existing FAQ content in FAQ schema	Quick
Content Readiness	Medium	Break wall-of-text paragraphs into 2–3 sentence passages	Medium
Content Readiness	Medium	Add a tl;dr summary block to long articles	Quick

The most common Top Fixes

Discoverability

robots.txt blocks AI user agents — explicit Disallow for GPTBot, Google-Extended, PerplexityBot, ClaudeBot. Often inherited from a copy-pasted template; remove unless intentional.
Missing llms.txt — a 5-minute fix; add a root-level llms.txt summarising your brand and key URLs.
Sitemap missing or stale — generate and submit a fresh sitemap.xml.
JS-only rendering on key pages — if a page requires JS to show content, AI crawlers often miss it. SSR or pre-render the critical pages.

Authority

No Organization schema — add Schema.org Organization JSON-LD with logo, sameAs, and contact.
No FAQ schema on FAQ pages — wraps your existing FAQ content; doesn't require new copy.
Missing canonical tags — common on duplicate URL patterns; AI models penalise duplicate signals.
No breadcrumb markup — even a small BreadcrumbList JSON-LD lifts the score.

Content Readiness

Multiple H1s or no H1 — use exactly one per page.
Wall-of-text paragraphs — break into 2–3 sentence paragraphs with clear sub-headings; AI models cite shorter, scannable passages more often.
Missing tl;dr / summary block at the top of long articles.
Thin internal linking between related articles.

Acting on fixes

Each Top Fix row links directly to the affected URL and shows the offending markup or absence. Where possible, Pranas includes a copy-pasteable code snippet (e.g., the JSON-LD block to add).

Re-auditing after fixes

Wait the full rate-limit hour, deploy your changes, flush any CDN cache, and re-run. The re-audit will show:

Resolved fixes drop off the list
New lower-severity issues may surface (this is expected — the bar rises as your score climbs)
The pillar score should move within hours, not days, because the audit re-fetches live content (no third-party indexing lag)

AI Search Audit (GEO Audit)
Audit rate limit
Citation optimization tactics