www.anthropic.com

Report from 8/10/2026, 11:02:18 AM https://www.anthropic.com
Latest run · lab, cold cache
49
8/10/2026
28-day score · p75 · the standard
49
31 runs
CRR90%latest
SSD7%latest
TC97 toklatest
TTFUT27 ms28-day p75

Scored by v3 · source-of-truth hashes: score db860d6ac94e · thresholds e94f8b33e500 — verifiable against the canonical scorer.

The 28-day score is the p75 of nightly runs — the stable number to cite. Deterministic metrics (CRR/SSD/TC) show their latest value (they move only when the site changes); timing (TTFUT) and answer-fidelity (AF) are smoothed by 28-day p75 — the same lab-vs-field split Core Web Vitals uses. Synthetic daily measurement, not real-user field data.

Core Agent Vitals badge  Embed this badge

Show your agent-readiness score anywhere — it links back to this report.

[![Core Agent Vitals](https://agentvitals.dev/badge/anthropic.com.svg)](https://agentvitals.dev/results?url=https%3A%2F%2Fwww.anthropic.com)
<a href="https://agentvitals.dev/results?url=https%3A%2F%2Fwww.anthropic.com"><img src="https://agentvitals.dev/badge/anthropic.com.svg" alt="Core Agent Vitals" height="20"></a>
What AI tells your customers about youAgent confidence: LOW
🟡Business nameHome \ Anthropic · guessed from page text (no structured data)
Categorynot found
Pricenot applicable · not applicable to this page type
Locationnot applicable · not applicable to this page type
Hoursnot applicable · not applicable to this page type
Productsnot applicable · not applicable to this page type
🟡DescriptionAnthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. · guessed from page text (no structured data)

An agent is likely to fabricate missing details rather than say “I don’t know”. 0/3 applicable facts come from machine-readable structured data.

We recovered only a shell of this page (under 200 tokens) — likely a soft bot-block or a client-rendered app that served our scanner almost no content. The metrics below reflect that shell, not your real site; the score is capped until an agent can retrieve real content.
49
Overall score
weighted CAV (0–100)
FAIL
0–4950–8990–100

Metrics

90%
CRR Content Recovery Needs work
0.07
SSD Semantic Signal Density Poor
97 tok
TC Token Cost Good
27 ms
TTFUT Time to First Useful Token N/A

Token Cost breakdown

Where the page's tokens go (≈4,240 across regions). Most tokens are real content — the agent isn't paying much for chrome.

Content
100% · 4,240
Chrome (nav / header / footer)
0% · 0
Boilerplate (cookie / ad)
0% · 0
Other
0% · 0

Final screenshot

Final screenshot of https://www.anthropic.com

Diagnostics

high SSD Low signal-to-noise for agents

content vs chrome/boilerplate

Evidencesignal 0.11 · JSON-LD 0/1 · missing: structured-data
ImpactAgent spends tokens parsing nav/boilerplate instead of content.
Effort30–90 min

Fix: Wrap the real content in <main>/<article>, cut repeated nav/boilerplate, and keep the primary content dense and early in the DOM.

medium CRR Content is hidden behind JavaScript

pre-JS raw HTML

Evidence10% of content requires JS
ImpactA non-rendering agent never sees the JS-injected content.
Effort1–4 h

Fix: Server-render or statically generate the main content so a non-JS agent still receives it; make client rendering a progressive enhancement, not the source of truth.

Rendered profile: headless

Agent Discoverability 76/100 · Needs Work

Access & discovery checks — separate from the gated CAV metrics above. Click an issue for business impact, what we measured, and how to fix. · Take the Agent Readiness course →

Agent files & endpoints

llms.txt Absent at /llms.txt and /.well-known/llms.txt Learn →
robots.txt (AI bots) Major AI bots allowed Learn →
sitemap.xml Found at /sitemap.xml Learn →
JSON-LD structured data No JSON-LD found Learn →
~ agents.json Absent (emerging standard) Learn →
~ WebMCP endpoint Absent (emerging standard) Learn →
~ OpenAPI / API docs No OpenAPI/Swagger found Learn →

Issues (5)

llms.txt present high impact Absent at /llms.txt and /.well-known/llms.txt

Business impact llms.txt is the robots.txt for AI: it tells agents what your site is, what matters, and where to find it. Without it AI guesses — and guessing means inaccurate recommendations and lost visibility.

What we measured We fetch /llms.txt and /.well-known/llms.txt and validate the spec (H1 title + a one-line blockquote summary). We also note /llms-full.txt (your full content as Markdown).

How to fix Create /llms.txt with a short summary + key pages; optionally /llms-full.txt with full content in Markdown.

Learn how to implement →

# Your Site
> One-line description for AI agents.

## Key pages
- /products — catalog
- /pricing — plans
- /docs — documentation

Spec: https://llmstxt.org

Structured data (JSON-LD) medium impact No JSON-LD found

Business impact Schema.org JSON-LD tells agents what a page IS (product, article, business) with typed fields (price, rating, hours). Without it agents extract less reliably.

What we measured We parse <script type=application/ld+json>, validate it, and check for populated @type fields.

How to fix Add JSON-LD: Organization/LocalBusiness on the homepage, Product on product pages, Article on posts.

Learn how to implement →

<script type="application/ld+json">{"@context":"https://schema.org","@type":"Organization","name":"Your Co","url":"https://example.com"}</script>

Spec: https://schema.org/

~ agents.json discovery low impact Absent (emerging standard)

Business impact agents.json describes what your site can DO for agents (services, endpoints, capabilities) — an emerging discovery standard. Early adopters get native agent integration.

What we measured We check /agents.json and /.well-known/agents.json for a valid configuration.

How to fix Publish /agents.json describing your site's capabilities and actions.

Learn how to implement →

Spec: https://github.com/wild-card-ai/agents-json

~ WebMCP endpoint low impact Absent (emerging standard)

Business impact WebMCP lets agents call actions on your site directly (book, buy, query) instead of scraping the DOM. Early adopters get native AI-agent interoperability.

What we measured We check /.well-known/webmcp and /webmcp.json for a valid actions array.

How to fix Add a WebMCP endpoint exposing your key actions to agents.

Learn how to implement →

Spec: https://webmcp.org

~ API documentation low impact No OpenAPI/Swagger found

Business impact Programmatic agents prefer a typed API. An OpenAPI/Swagger spec lets them integrate without scraping.

What we measured We probe /openapi.json, /swagger.json, /api-docs and /.well-known/openapi.json.

How to fix Publish an OpenAPI spec at a well-known path.

Learn how to implement →

Spec: https://www.openapis.org/

Passed audits (6)

✓ robots.txt allows AI bots✓ No CAPTCHA wall✓ No content-blocking cookie wall✓ No login wall on public content✓ XML sitemap present + fresh✓ Server response (TTFB)

Transport & Trust (SEC 1.0.0)

HTTPS, HSTS, CSP, sniffing, referrer and CORS posture. Diagnostic only — this does not affect the CAV score. A security header does not make a page more legible to an agent, so scoring it would reward a CDN toggle that changes nothing an agent can recover. We measure it and say so.

50Transport posture (0–100, unscored)
1pass
3warn
1fail
Per-header findings (6)
HeaderEvidence
✅ HTTPSserved over HTTPS
⚠️ HSTSmax-age=3600 is below the 180-day baseline
⚠️ Content-Security-Policyscript-src allows 'unsafe-inline'
❌ X-Content-Type-Optionsmissing nosniff
⚠️ Referrer-Policyno referrer-policy header (browser default applies)
➖ CORS exposureno CORS headers on the document (normal for an HTML page)
Full profile — how to improve · unused JS · network · timing

A deeper scan (a second render, ~30–60s): network waterfall, unused JavaScript, long tasks, and prioritized fixes. Runs only when you ask; the result is cached so it never re-runs.

Analyzing…
running mobile + desktop · ~30s