Metrics & Audits

Checks the machinery search engines rely on: robots.txt and sitemap coverage, canonical tags, indexability, redirects, HTTPS, hreflang and pagination, and clean URL structure across every crawled page.

Evaluates the elements you control on each page — title tags and meta descriptions (length and uniqueness), a single well-formed H1, heading hierarchy, and image alt text.

Looks at whether pages carry enough substantive text to rank, the ratio of real content to markup, and how readable that writing is for a general audience.

Measures real-world speed using Core Web Vitals — largest contentful paint, layout shift, and interactivity — alongside page weight and load time, so you see what actually slows visitors down.

A passive, no-touch review of HTTPS enforcement, HSTS, the Content-Security-Policy and other security headers, mixed content, and email records like SPF and DMARC. We never probe or attack a site.

Flags common barriers that also hurt SEO — missing image alt text, unlabeled form fields, poor heading order, and language attributes — so your pages work for more people and more crawlers.

Confirms the essentials of a mobile-ready page, starting with a correct viewport meta tag and touch-friendly layout signals, since Google indexes the mobile version first.

Answer-engine optimization asks whether a machine could lift a clean, self-contained answer from your page for featured snippets, People Also Ask, and AI Overviews. We look at the text that actually follows each question-style heading — not just whether the question exists.

Generative-engine optimization reads the markup that identifies the organization behind your site — Organization schema, the sameAs links to your official profiles, author signals and modified dates — plus how concrete the writing is (named figures, dates, outbound sources). No AI engine documents sameAs or a Wikipedia entry as a citation factor; what unambiguous entity markup reliably does is let anything parsing the page tell which organization it is reading about.

AI optimization is about machine-readability for LLM crawlers: whether your content is well-structured and served without heavy JavaScript rendering, and whether AI crawlers are blocked in your robots.txt. Two things we report but never score — whether an /llms.txt file exists, an optional index of your own key pages that no major AI search engine has committed to reading, and any Content-Signal line in robots.txt, which is where you state how you want your content used.

Scores the trust signals Google associates with quality content — author bylines and credentials, about and contact pages, outbound links to authoritative sources, and Person or Organization schema.

Detects published and modified dates across your pages to gauge how current your content is, since stale pages lose ground in fast-moving topics.

Compares pages across the crawl to find exact and near-duplicate content that can split ranking signals or waste crawl budget.

Checks whether pages use meaningful HTML5 elements — header, nav, main, article, section, footer — rather than a wall of generic divs, which helps both assistive tech and machine parsing.

Validates the structured data (JSON-LD) on your pages — the types present, the fields Google requires for each, and the values that make a block invalid — so a machine can tell what each page represents. Types Google still shows a rich result for (Article, Product, Local business, Breadcrumb, Event, Recipe) are checked against its requirements; FAQPage and HowTo are flagged instead, since Google removed those rich results from Search in May 2026.

Reviews the Open Graph and social meta tags that control how your pages look when shared, plus linked social profiles that reinforce your brand entity.

For sites that look like a local business, audits name-address-phone consistency, LocalBusiness schema, maps, and opening hours. Sites with no physical presence are scored neutrally, never penalized.