AX 감사 보고서

https://edenhq.com

August 12, 20263157ms response

56AX score / 100

Needs work

Readiness diagnosis

This site needs work before agents can use it reliably. Address the priority findings to improve readiness.

0개 심각

7 warnings

22개 통과

Current constraintAgent Integration22%

Five readiness layers

Readiness orbit

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

Evidence profile

29 checks recorded

Passed vs. material gaps

Critical

Warnings

Passed

Discovery

3.5 / 13 weighted points

27%

Identity

11.8 / 22 weighted points

54%

Access

28.3 / 31 weighted points

91%

Agent Integration

Current constraint

5.2 / 24 weighted points

22%

User Experience

7.3 / 10 weighted points

73%

Start here

Top Priorities

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

JSON-LD found but no business schema (found: unknown)

구조화된 데이터

Review

llms.txt found but format is incomplete

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

Only 4% of images have alt text (2/56)

콘텐츠 품질

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

Found 1 JSON-LD structured data block

JSON-LD found but no business schema (found: unknown)
Add a business-specific schema type (LocalBusiness, Organization, Product, Service) to help AI agents understand what your business offers.

Schema has 0 fields — consider adding more for better AI comprehension

OpenGraph tags complete (title, description, image)

Meta tags complete (title, description, canonical)

JSON-LD schema missing @context or @type

llms.txt found but format is incomplete
Your llms.txt should have: # Title, > description blockquote, ## Sections, and [links](url). See https://llmstxt.org for the full spec.

llms-full.txt also found (two-file mode)

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.xml found and valid

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

HTML semantic structure is well-formed

Only 4% of images have alt text (2/56)
Add descriptive alt attributes to all <img> tags. Example: <img alt="Description of image content" src="..." />

Sufficient text content available for AI extraction

FAQ-like content found but no FAQ schema

2 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

Response time is 3.2s — slower than agents prefer

Lean HTML payload (147KB)

Response is compressed (br)

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

Entry URL redirects before serving — adds latency for agents

Author/publisher identity declared in schema

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"

Sitemap shows content updated within the last 6 months

Footer/copyright year is current

HTTPS enabled

SSL certificate valid

Privacy policy link found

Terms of service link found

edenhq.com

https://edenhq.com

Readiness orbit

Top Priorities

Findings and fixes

All Findings

Turn audit findings into an agent-ready funnel.

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