agentspeed.
← all tools
Tool

Agent Readability Scanner

Score whether an AI agent can understand a page WITHOUT executing JavaScript. Fetches the URL once, parses the SSR HTML, and grades seven axes deterministically: text content, heading structure, metadata quality, internal links, schema presence, and a heuristic JS-dependency estimate. Returns an agent-perspective summary of what a bot reading raw HTML would actually understand.

Tool
›
https://github.comHTTP 200
Agent readability score
81/ 100
8,186 chars texttext/html ratio 0.01JS dep 0.40
Agent-perspective summary

An AI agent reading this page would identify it as "GitHub · Change is constant. GitHub keeps you ahead. · GitHub". Join the world's most widely adopted, AI-powered developer platform where millions of developers, businesses, and the largest open source community build software that advances humanity. It can ground answers in approximately 8,186 characters of body text. First 240 chars: "GitHub · Change is constant. GitHub keeps you ahead. · GitHub Skip to content Navigation Menu Toggle navigation Sign in Platform AI CODE CREATION GitHub Copilot Write better code with AI GitHub Copilot app Direct agents from issue to merge…".

Detected signals

  • <title>GitHub · Change is constant. GitHub keeps you ahead. · GitHub
  • meta descriptionJoin the world&#39;s most widely adopted, AI-powered developer platform where millions of developers, businesses, and the largest open source community build software that advances humanity.
  • <link rel=canonical>https://github.com
  • meta robots—
  • H1 / H2 / H3 count4 / 10 / 16
  • links (internal / total)103 / 144
  • JSON-LD blocks0

Findings

Text-to-markup ratiocontent.text_ratio

1% of the page is readable text (ratio 0.01); the rest is markup and scripts.

fix Server-render the primary copy so readable text outweighs markup.

JavaScript dependencycontent.js_required_for_primary_content

Heuristic dependency score 0.40/1.00 from SSR text volume, text/script ratio, and JS-required placeholders.

fix Server-render primary content; treat JavaScript as enhancement, not a requirement.

Heading structurecontent.headings_hierarchy

4 H1 · 10 H2 · 16 H3.

fix Use exactly one <h1> and section the page with <h2>s.

Title tagmarkup.title

61 characters: "GitHub · Change is constant. GitHub keeps you ahead. · GitHub".

fix Set a unique 30–60 char <title>: "Page topic, Brand".

Meta descriptionmarkup.meta_description

190 characters.

fix Add <meta name="description"> with a 120–160 char summary.

Canonical declaredmarkup.canonical

https://github.com

103 internal linkslinks.internal

Of 144 total links. Agents follow internal links to ground answers.

No JSON-LDstructured_data.jsonld_present

No structured data; agents infer publisher, type, and authorship from prose.

Result summary

Copyable plain-text summary for sharing with engineers / SEO leads.

AgentSpeed Agent Readability Scanner
Target: https://github.com
HTTP: 200
Score: 81/100
Text chars: 8186  |  text/html ratio: 0.01  |  JS dep: 0.40

Findings:
  [PASS] 8,186 chars of server-rendered text (content.text_amount)
  [PASS] Title present (metadata.title)
  [PASS] Meta description present (metadata.description)
  [PASS] Canonical declared (metadata.canonical)
  [WARN] 4 <h1> tags (headings.h1)
  [PASS] 10 H2 / 16 H3 (headings.h2)
  [PASS] 103 internal links (links.internal)
  [FAIL] No JSON-LD (schema.present)
  [WARN] Moderate JS dependency (js.dependency)

Run again at: https://agentspeed.com/tools/agent-readability-scanner
Watch this URL — get alerted when this changes

Turn this one-off check into a scheduled watch. We re-run it, diff the result, and alert you on a regression through the same channels as your agent alerts. Watches are a paid feature.

Manage watches at /watches. You’ll be asked to sign in if you haven’t already.

Examples

Click an example to run the tool with pre-filled inputs.

Why this matters for AI agents

Most agent-visibility problems are SSR problems. A site that hydrates everything client-side ships an empty shell to GPTBot and ChatGPT-User; a site that puts the value prop, pricing, and CTAs in the initial HTML response ships a real page. The difference shows up in citation rate.

This tool runs in your browser’s tab and reports what the bot actually receives. No headless browser involved. The JS- dependency score is a heuristic from the SSR HTML, not a real render comparison. Flagged in the result.

Common fixes
Empty shell page
Server-render the hero, value props, and pricing. Treat JavaScript as enhancement; the page should be useful with JS disabled.
Missing or thin <title>
Set a unique 30–60 char <title> per page. Format: "Page topic, Brand". Agents quote titles verbatim.
No JSON-LD
Add Organization + WebSite blocks site-wide; add page-kind schemas (Product, Article, FAQPage) per page. The structured-data validator generates copyable templates.
Multiple H1s
One H1 per page. Multiple H1s confuse agents that pick the first as the topic; the rest are weighted as section headings.
Few internal links
Cross-link related content from the body. Agents follow internal links to ground answers; thin internal linking caps citation breadth.
Linked rubric checks
FAQ
Why no headless browser?
Two reasons. First, the question this tool answers is "what does an agent reading the raw HTML response see?", and running a browser would mask that. Second, headless rendering per request would balloon latency and infrastructure cost. The full AgentSpeed scan does include a headless render pass; this tool focuses on the SSR-side signals.
How is JS dependency calculated?
A 0–1 heuristic. Penalties for: short SSR text content (<800 chars adds 0.4, <2,000 adds 0.15), low text-to-HTML ratio (<5% adds 0.4, <15% adds 0.2), and "needs JavaScript" / "Loading…" placeholder phrases in the body (adds 0.3). Capped at 1.0. Anything above 0.6 is treated as fail.
What does "agent perspective summary" mean?
A deterministic one-paragraph reconstruction of what an AI agent reading the SSR HTML would actually be able to summarise about the page. For thin pages, it admits the agent could not summarise the page; for content-rich pages, it reflects the title, description, and a snippet from the body.
Is this the same as the structured-data validator?
Different focus. The validator checks whether your JSON-LD parses and validates; this scanner checks whether agents can read your page at all. JSON-LD is one of several signals here, alongside text content, headings, and JS dependency.
Run a full agent-readiness scan
Full scan

Score the entire site against 30 agent-readiness checks across discoverability, readability, structured data, actionability, and performance.

Get the full report for github.com →