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Compare measured web signals

Compare purpose profiles and measured stable-core coverage under one methodology. The static result does not predict citation or agent task outcomes.

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Why compare?

A side-by-side view can reveal differences in measured web-signal coverage. Numeric comparisons are shown only when methodology and detailed evidence match.

Spot competitive gaps

Compare which structured-data and discovery signals each scan observed. Presence or absence does not predict citation outcomes.

Prioritize what matters

Compare measured point gaps across five categories when the scans are methodologically compatible. Weights express versioned policy, not causal visibility impact.

Track your progress

Re-run scans after changes to observe differences in measured coverage. Score changes do not establish competitive or agent outcomes.

What the methodology measures

The score summarizes measured coverage of applicable web signals for discovery, structured data, semantics, protocols, and security. It does not predict agent task success.

PURPOSE PROFILES
4

Compare four purpose-specific interpretations before the general score

EXPERIMENTAL EVIDENCE
0

Browser outcomes and WebMCP observations do not affect the stable score

METHODOLOGY
V

Only scores from the same methodology version are compared

REGISTERED CHECKS
70

Stable, bonus, and informational checks are versioned explicitly

Understand AI citations

How do AI systems decide which websites to cite? These deep dives reveal the mechanics behind the three biggest AI search engines.

Does Schema Markup Get You Cited by AI? What the Data Actually Shows
9 min read

Does Schema Markup Get You Cited by AI? What the Data Actually Shows

A 2026 Ahrefs study tracked 1,885 pages adding schema markup, and AI-search citations barely moved. We separate correlation from causation: what structured data is actually proven to do, what really drives citations, and where to spend your effort.

ai-agents seo getting-started
Content Negotiation for AI Agents: Why Sentry Serves Markdown Over HTML
9 min read

Content Negotiation for AI Agents: Why Sentry Serves Markdown Over HTML

Sentry co-founder David Cramer shows how content negotiation — a 25-year-old HTTP standard — saves AI agents 80% of tokens. We break down the implementation: Accept headers, markdown delivery, authenticated page redirects, and what this means for every website preparing for agent traffic.

ai-agents seo getting-started
Cloudflare /crawl Endpoint: One API Call to Crawl Any Website
9 min read

Cloudflare /crawl Endpoint: One API Call to Crawl Any Website

Cloudflare launched a /crawl endpoint that crawls entire websites with one API call — returning HTML, Markdown, or AI-extracted JSON. We break down what this means for AI agent readiness: why your robots.txt, sitemap, semantic HTML, and server-side rendering now matter more than ever.

ai-agents seo getting-started

What we compare

Compare purpose profiles and measured stable-core coverage of applicable signals. No numeric verdict is shown when evidence is incomplete.

30%

AI CONTENT DISCOVERY

Discovery has the highest configured weight in this methodology. Compare observed robots.txt policies, sitemap presence, and llms.txt signals.

  • robots.txt
  • AI Crawler Directives
  • XML Sitemap
  • llms.txt
  • Meta Robots
  • HTTP Bot Access
20%

AI SEARCH SIGNALS

Structured data makes content machine-readable for agents and search indexes. Compare JSON-LD coverage, Schema.org vocabulary, and entity linking across both sites.

  • JSON-LD
  • Schema.org Types
  • Entity Linking
  • Primary Page Schema
  • Schema Validation
  • Organization Schema
20%

CONTENT & SEMANTICS

Browser agents may combine the DOM, accessibility tree, and screenshots. Compare heading hierarchy, semantic markup, and meaningful initial HTML for fetch-only access.

  • SSR Detection
  • Heading Hierarchy
  • Semantic HTML
  • ARIA Landmarks
  • Alt Text
  • Language
  • Link Text
15%

AGENT PROTOCOLS

Compare supported A2A Agent Card, MCP Discovery, OpenAPI, and agents.json signals when the scans are methodologically compatible.

  • A2A Agent Card
  • MCP Discovery
  • OpenAPI
  • agents.json
15%

SECURITY & TRUST

Compare measured HTTPS, HSTS, CSP, and security-header coverage. The category weight is a versioned policy choice, not a prediction of agent trust.

  • HTTPS
  • HSTS
  • CSP
  • X-Content-Type-Options
  • X-Frame-Options
  • CORS
  • Referrer-Policy

Experimental WebMCP evidence

WebMCP observations are reported separately as experimental evidence and do not affect the stable score.

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Compare measured coverage and get a prioritized action plan.

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Rankings
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Rankings

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About
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About

Why AI agent readiness matters and how we measure it. Understand our methodology and scoring system.