Bot Detection
Server-side detection and classification of AI crawlers visiting a website. Part of the Signals layer in 3LA. Logs which AI systems crawl which pages, at what frequency, and whether they access machine-readable files like /entitymap.json and /llms.txt. Enables measurement of actual EntityMap consumption by AI systems.
This term is part of the 3LA EntityMap → /entitymap.html
Related terms
Log Analyzer
toolA 3LA tool that parses server logs to identify which AI agents and search bots visit your site – and what they are looking for but not finding.
AI Dark Traffic
GEOTraffic and brand exposure originating from AI models that is not traceable in standard analytics tools – users who discover you via ChatGPT or Perplexity do not appear as AI referrals in GA4 or GSC.
First-View Content
L3Content visible within the first 2,000 characters of extracted text without JavaScript rendering – AI crawlers do not run JS, and content requiring rendering is invisible to them regardless of quality.
L3 AI Layer
coreThe third layer in the Three-Layer Approach framework. Measures 12 metrics including Structural Proof Gap, Citation-Worthiness, Citation Readiness, Answer-First Format, LLMs.txt, and Chunk Optimization. Citation rate measured across ChatGPT (GPT-5.2), Claude Sonnet 4.6, Gemini 3.1 Pro in every audit. Weight: 30% of LayerScore. Platform average L3: 68/100. Typical lift after optimisation: +28 points.
Structural Proof Gap
metricA 3LA metric measuring how many of a page's intent-critical claims — price, service, FAQ, rating, organization, location — are proven with Schema.org markup rather than merely asserted in prose. Platform data: 76.2% low gap, 23.8% medium gap across 909 claims tracked. An LLM cites what it can verify.
