Automated llms.txt
Manifest and full-text variants, token-budgeted, kept in sync with content.
AEO
AI-engine optimization
Get cited when ChatGPT, Perplexity, Gemini and Claude answer buying questions.
What it does
Search is shifting from ten blue links to one AI answer. The AEO module does four things: generates and maintains llms.txt (plus a full-text variant) to spec; scores every page against ten AI-readability checks with a 0-100 score and A-F grade; feeds a target-question bank to multiple AI engines on schedule, recording whether you were cited, at what position, and which competitor was; and parses server logs to show what GPTBot and PerplexityBot actually crawled.
Together those four turn AI visibility from folklore into an operable metric: which pages parse, which questions already cite you, and whether the bots have come.
A newer layer reads your pages the way an engine would: a passage-level citability audit scores every article paragraph by paragraph for whether an AI answer could quote it verbatim, naming the weakest passage to rewrite — pure rules, no model cost, with CJK auto-adapted; a crawler-access audit checks whether robots.txt shuts the major AI engines out, with an access score and fixes; and citation monitoring expands to five channels, two of them native citation attribution from real AI answer engines, recording who got cited when you didn't.
Core capabilities
Page-to-passage scoring
Ten readability checks and an A-F grade per page, then a passage-level audit of what an AI could quote verbatim — weakest passage named.
Cross-engine citation tracking
Scheduled checks record citation, position, snippet and cited competitors.
Feature checklist
- Ten checks: meaningful H1, meta description, schema, content depth, semantic structure, FAQ, outbound citations, internal links, title specificity and more
- Three check channels: search-augmented model, Tavily retrieval, main-model simulation
- Auto-check daemon sweeps the question bank every 24 hours by default
- Bot-traffic analysis identifies real crawls by ChatGPT-User, PerplexityBot, OAI-SearchBot
- Top-cited pages and visibility trends aggregate on one board
- Passage-level citability audit: each passage scored 0-100 across answer-block quality, self-containment, structure, statistic density and uniqueness; passages that clear the bar are marked quotable-verbatim — pure heuristics, no model cost, CJK auto-adapted
- Crawler-access audit: each major AI crawler judged allowed/partial/blocked with a 0-100 access score and robots.txt fixes, one click to an ops task
- Citation monitoring across five channels, two of them native attribution from real AI answer engines; cited competitor domains recorded on a miss; engine keys hot-configured in the console, unconfigured engines skipped without error
Want to see this module run?
Book a demo and we'll run this module on real data.