Rapport d'audit AX

https://edx.org

August 12, 20261137ms response

55AX score / 100

Needs work

Readiness diagnosis

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

0 critique

10 warnings

21 réussi

Current constraintAgent Integration14%

Five readiness layers

Readiness orbit

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

Evidence profile

31 checks recorded

Passed vs. material gaps

Critical

Warnings

Passed

Discovery

5.7 / 13 weighted points

44%

Identity

10.5 / 22 weighted points

48%

Access

27.7 / 31 weighted points

89%

Agent Integration

Current constraint

3.3 / 24 weighted points

14%

User Experience

8 / 10 weighted points

80%

Start here

Top Priorities

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

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

Données structurées

Review

Missing OpenGraph tags: og:image

Données structurées

Review

No sitemap.xml found

Interaction avec l'agent

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

Données structurées

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

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

Meta tags complete (title, description, canonical)

JSON-LD schema missing @context or @type

llms.txt found but format is incorrect

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.

No sitemap.xml found
Create a /sitemap.xml file listing all your important pages. Also declare it in robots.txt:
Sitemap: https://yoursite.com/sitemap.xml

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

Checkout path found, but no machine-readable prices (Offer schema)

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: <nav>, <h1>
Add missing semantic HTML elements: <nav>, <h1>

98% of images have alt text (50/51)

Sufficient text content available for AI extraction

3 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.

Contact information detected (phone, address)

Fast response time (1137ms)

Very large HTML payload (2310KB) — agents may truncate it
Trim your initial HTML payload — defer non-critical markup and avoid inlining large data blobs. Agents truncate very large documents.

Response is compressed (gzip)

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

Security headers present (HSTS + Content-Security-Policy)

Content dates (dateModified/datePublished) present in schema

Footer/copyright year is current

HTTPS enabled

SSL certificate valid

Privacy policy link found

Terms of service link found

edx.org

https://edx.org

Readiness orbit

Top Priorities

Findings and fixes

All Findings

Turn audit findings into an agent-ready funnel.

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