Informe de auditoría AX

https://atlassian.com

August 12, 20261668ms response

58AX score / 100

Needs work

Readiness diagnosis

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

0 crítico

8 warnings

24 aprobado

Current constraintAgent Integration36%

Five readiness layers

Readiness orbit

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

Evidence profile

32 checks recorded

Passed vs. material gaps

Critical

Warnings

Passed

Discovery

4.9 / 13 weighted points

38%

Identity

12.6 / 22 weighted points

57%

Access

25.4 / 31 weighted points

82%

Agent Integration

Current constraint

8.7 / 24 weighted points

36%

User Experience

6 / 10 weighted points

60%

Start here

Top Priorities

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

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

Datos estructurados

Review

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

Interacción con el agente

Review

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

Actionability

Review

Missing semantic HTML: <header>

Calidad del contenido

Review

Only 33% of images have alt text (19/57)

Calidad del contenido

Review

Explore the audit

Findings and fixes

Datos estructurados

Authoritativeness

All Findings

robots.txt allows all major AI crawlers

Page returns HTTP 200

Page content available without JavaScript

Cookie consent wall detected — may block AI crawlers

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

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.

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

Page mentions MCP support but no MCP endpoint found

API documentation links found

Sitemap found at https://www.atlassian.com/blog/post-sitemap.xml (declared in robots.txt)

Schema.org potentialAction defined — agents know what actions are available

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 33% of images have alt text (19/57)
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

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

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.

Contact information detected (phone, address)

Response time is 1.7s — acceptable, could be faster

Very large HTML payload (2371KB) — 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 (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

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

atlassian.com

https://atlassian.com

Readiness orbit

Top Priorities

Findings and fixes

All Findings

Turn audit findings into an agent-ready funnel.

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