AX Audit Report

https://turingcollege.com

August 12, 20261662ms response

62AX score / 100

Needs work

Readiness diagnosis

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

0 critical

7 warnings

24 passed

Current constraintAgent Integration28%

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

6.7 / 13 weighted points

51%

Identity

11.8 / 22 weighted points

54%

Access

29 / 31 weighted points

94%

Agent Integration

Current constraint

6.7 / 24 weighted points

28%

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)

Structured Data

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

Missing semantic HTML: <header>

Content Quality

Review

Only 59% of images have alt text (111/189)

Content Quality

Review

Explore the audit

Findings and fixes

Structured Data

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 with correct format

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

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

Only 59% of images have alt text (111/189)
Add descriptive alt attributes to all <img> tags. Example: <img alt="Description of image content" src="..." />

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)

2 industry directory links found

Response time is 1.7s — acceptable, could be faster

Lean HTML payload (258KB)

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

turingcollege.com

https://turingcollege.com

Readiness orbit

Top Priorities

Findings and fixes

All Findings

Turn audit findings into an agent-ready funnel.

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