Search discovery now includes semantic retrieval and AI-generated answers alongside traditional indexing. Scanlyst evaluates structured data, crawl hierarchy, semantic headings, and AI crawler accessibility to improve how clearly machines can understand and cite your public content.
Parsed cleanly by LLM context scrapers
Validated against Schema.org 24.0
Robots, canonicals & sitemap alignment
Optimized for Perplexity & Claude citations
Comprehensive validation of traditional search engine factors alongside cutting-edge Answer Engine Optimization (AEO) protocols.
Verifies content chunk readability, factual density, and semantic entity clarity for ChatGPT-Search, Perplexity, and Claude scrapers.
Audits canonical links, redirection chains, indexing directives (noindex/nofollow), and XML sitemap synchronization.
Validates Organization, Product, Article, and FAQ schema against strict Schema.org standards to power rich snippets in search results.
Checks og:title, og:image dimensions, Twitter Cards, and fallback meta tags to ensure viral previews render impeccably across social platforms.
Ensures logical outline hierarchy with exactly one primary H1, zero skipped heading levels, and keyword-aligned section titles.
Inspects user-agent disallows for Googlebot, Bingbot, GPTBot, ClaudeBot, and PerplexityBot to prevent accidental traffic blackouts.
Simulating entity resolution and citation generation across Claude and Perplexity agents.
Engineered in lockstep with official search engine webmaster guidelines and open-source semantic web specifications.
Strict adherence to indexing, crawlability, and algorithmic spam avoidance policies.
Universal structured vocabulary for search engines and generative AI agents.
Standards-compliant handling of GPTBot, OAI-SearchBot, and AI attribution headers.
Ensures programmatic document hierarchy for high accessibility and crawler comprehension.
Audit your domain for technical SEO bottlenecks and Generative Engine Optimization readiness in one seamless scan.