AX 감사 보고서

https://empirical.health

August 12, 2026956ms response

44AX score / 100

미흡

Readiness diagnosis

This site is not ready for AI agents yet. Resolve the critical access and understanding gaps first.

1개 심각

6 warnings

16개 통과

Current constraintDiscovery11%

Five readiness layers

Readiness orbit

The shape reveals where an agent journey breaks down, from finding the site to completing useful work.

Evidence profile

23 checks recorded

Passed vs. material gaps

Critical

Warnings

Passed

Discovery

Current constraint

1.4 / 13 weighted points

11%

Identity

3.3 / 22 weighted points

15%

Access

29 / 31 weighted points

94%

Agent Integration

3.1 / 24 weighted points

13%

User Experience

6.7 / 10 weighted points

67%

Start here

Top Priorities

Select the highest-impact Findings to include in your Fix Plan.

No JSON-LD structured data found

구조화된 데이터

Review

Missing OpenGraph tags: og:description

구조화된 데이터

Review

No llms.txt file found — AI agents cannot discover your services

에이전트 상호작용

Review

No Schema.org potentialAction — agents can't tell what they can do on your site

Actionability

Review

No form or direct contact path — agents have no way to convert here

Actionability

Review

Explore the audit

Findings and fixes

구조화된 데이터

Authoritativeness

All Findings

robots.txt allows all major AI crawlers

Page returns HTTP 200

Page content available without JavaScript

No CAPTCHA or bot protection detected

No JSON-LD structured data found
Add JSON-LD structured data to your page <head>:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Business",
  "url": "https://yoursite.com",
  "description": "What your business does"
}
</script>

Missing OpenGraph tags: og:description
<meta property="og:description" content="..." />

Missing meta tags: meta description

No llms.txt file found — AI agents cannot discover your services
Create a /llms.txt file at your site root:

# Your Business Name

> Brief description of your business.

## Services
- [Service 1](/service-1): Description
- [Service 2](/service-2): Description

See https://llmstxt.org for the full spec.

No MCP server or AI agent endpoint detected — agents cannot interact with your business
Set up a Model Context Protocol (MCP) server so AI agents can interact with your business directly. This allows agents to book appointments, check availability, and more.

With Dashform, you can add MCP support to your website in minutes — no coding required.

Alternatively, create /.well-known/ai-plugin.json for ChatGPT plugin compatibility.

Sitemap found at https://www.empirical.health/sitemap-index.xml (declared in robots.txt)

No Schema.org potentialAction — agents can't tell what they can do on your site
Add a potentialAction to your Schema.org JSON-LD so agents can act, e.g.:
"potentialAction": {
  "@type": "ReserveAction",
  "target": "https://yoursite.com/book"
}

No scheduling link found — agents can't book time with you directly

No form or direct contact path — agents have no way to convert here
Add an agent-usable conversion path — a contact form, a booking widget, or a Dashform AI funnel agents can complete on the visitor's behalf.

CTA buttons have descriptive labels

Missing semantic HTML: <main>
Add missing semantic HTML elements: <main>

100% of images have alt text (6/6)

Sufficient text content available for AI extraction

Heading levels skip (e.g., h1 directly to h3)

No social media links found

No Schema.org sameAs links — AI agents cannot verify your identity across platforms
Add sameAs to your Schema.org JSON-LD:
"sameAs": [
  "https://twitter.com/yourbrand",
  "https://linkedin.com/company/yourbrand"
]

No Google Maps or Business Profile presence detected — AI agents may not verify your location
Claim your Google Business Profile at https://business.google.com and embed a Google Maps link or iframe on your page. AI agents use Google Maps data to verify business locations.

Limited contact information — add phone, email, and address

Fast response time (956ms)

HTML payload is on the heavier side (546KB)

Response is compressed (br)

Caching headers present (Cache-Control/ETag/Last-Modified)

Entry URL redirects before serving — adds latency for agents

No author/publisher in schema — weak authorship signal
Add author and publisher to your Schema.org JSON-LD to establish credibility:
"publisher": { "@type": "Organization", "name": "Your Brand" }

No review/rating schema — agents can't surface your reputation

Partial security headers (HSTS only)

No dateModified/datePublished in schema — agents can't judge freshness
Add dateModified/datePublished to your Schema.org JSON-LD so agents can judge freshness:
"dateModified": "2026-01-15"

Footer/copyright year is current

HTTPS enabled

SSL certificate valid

Privacy policy link found

Terms of service link found

empirical.health

https://empirical.health

Readiness orbit

Top Priorities

Findings and fixes

All Findings

Turn audit findings into an agent-ready funnel.

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