CanAgentUse

CanAgentUse products

MCP ServerInstall CanAgentUse in your coding agent so scan findings become repo-ready fixes.View product WooCommerce PluginPublish UCP discovery and agent-ready commerce signals from WooCommerce without rebuilding checkout.View product Shopify PluginAdd UCP discovery, storefront metadata checks, and controlled cart-to-checkout flows for shopping agents.View product AgentReady CIScan commits and PRs, publish reports, and choose which agent-readiness failures should block merges.View product

CanAgentUse tools

UCP Suite

Validate Universal Commerce Protocol discovery, then test product search, carts, checkout links, and merchant handoff flows.

UCP ValidatorUCP Playground

MCP Playground

Connect to remote MCP servers, inspect tools and resources, test prompts, auth, headers, notifications, and JSON-RPC responses.

MCP Playground

A2A Playground

Inspect Agent Cards, validate advertised endpoints, and prepare safe requests for agent-to-agent workflows.

A2A Playground

Agent Website Viewer

Enter a public URL and see the roles, names, landmarks, controls, and blockers that shape how AI agents understand the page.

Agent Website Viewer
New Scan
https://www.bom.gov.au/
SCANNED
Jul 3, 2026, 12:55 AM
VISIBILITY
Public
SUITE2026.06.10
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59/100

OVERALL SCORE

Level 3, Bot-Aware

Moderate readiness for AI agents
AIDiscoverability37%Agent Easeof Use52%Security& Trust90%GEO, AIO, AEO49%SEO100%Performance58%Accessibility93%
  • AI Discoverability 37 out of 100
  • Agent Ease of Use 52 out of 100
  • Security & Trust 90 out of 100
  • GEO, AIO and AEO 49 out of 100
  • SEO 100 out of 100
  • Performance 58 out of 100
  • Accessibility 93 out of 100

CAPTURED SCREENSHOT

Captured website desktop screenshot

What AI sees of your website

Discover your weather | The Bureau of Meteorology favicon

Discover your weather | The Bureau of Meteorology

The Bureau of Meteorology web homepage provides the Australian community with access to weather forecasts, severe weather warnings, observations, flood information, marine and high seas forecasts and climate information. Products include w...

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Detailed report scores grouped by capability area
MetricScoreStatusPassedFailedWarningEvidence
AI Discoverability
37
Priority fix1410View details
Discoverability
47
Priority fix600
Content Readiness
17
Priority fix700
Bot Access Control
45
Priority fix110View details
Agent Ease of Use
52
Needs work300
Auth
47
Priority fix100
Skill Discovery
54
Needs work100
Google Agentic Browsing
61
Needs work100
GEO, AIO and AEO
49
Priority fix600
GEO Readiness
Not Applicable
Not Applicable200
AIO Readiness
Not Applicable
Not Applicable300
AEO Readiness
Not Applicable
Not Applicable100
SEO
100
Strong1000
SEO
100
Strong1000
Security & Trust
90
Strong2200
Security & Trust
90
Strong2200
Performance
58
Needs work1320View details
Performance
58
Needs work1320View details

Prioritized recommendations

Issues ranked by score impact

3 items need attention

AI DiscoverabilityBot Access ControlEstablished

AI bot rules in robots.txt

AI bot rules in robots.txt failed at "Classify AI crawler rules".

69 Fail

Needs attention

AI bot rules in robots.txt

Failed check
01

Issue

No explicit User-agent rules were found for major AI crawler tokens.

Details

02

Why it matters

AI crawler product tokens have different meanings. Explicit robots.txt groups make training, search, and retrieval access policy auditable for compliant crawler operators.

Check name

AI bot rules in robots.txt

Score

31/100

Status

fail

Category

Bot Access Control

Maturity

Established

Goal

Declare deliberate robots.txt rules for major AI training, AI search, user-triggered, and dataset crawlers.

Result

AI bot rules in robots.txt failed at "Classify AI crawler rules".

Validation steps

  1. Classify AI crawler rules

    No explicit User-agent rules were found for major AI crawler tokens.

    robots.txt lacks explicit AI crawler rules
Evidence log1 step · 6 lines
Classify AI crawler rules [fail]! No explicit User-agent rules were found for major AI crawler tokens.INFOClassify AI crawler rulesINFOParsing User-agent groups and Allow/Disallow records for known AI crawler tokens evaluatedPath="/"INFOEvaluating exact User-agent matches before wildcard fallback exactAiPolicyCount=0 totalCrawlerTokens=18FAILNo explicit AI crawler User-agent groups were found examplesExpected=["GPTBot","OAI-SearchBot","ClaudeBot","Google-Extended","CCBot"]FAILCompare explicit AI crawler coverage actual=0 expected="> 0 explicit non-search AI crawler policies" missingTokens=["GPTBot","OAI-SearchBot","ChatGPT-User","ClaudeBot","Claude-SearchBot","Claude-User","Google-Extended","Applebot-Extended","Amazonbot","Amzn-SearchBot","Amzn-User","PerplexityBot"]INFOResolved effective root-path policy for crawler tokens blocked=0 allowed=21 unspecified=0

PerformancePerformanceBrowser audit

Avoid large layout shifts

50 Fail

Check name

Avoid large layout shifts

Score

0/100

Status

fail

Device

desktop

Category

Performance

Estimated savings

5 layout shifts found

Fix guidance

These are the largest layout shifts observed on the page. Each table item represents a single layout shift, and shows the element that shifted the most. Below each item are possible root causes that led to the layout shift. Some of these layout shifts may not be included in the CLS metric value due to [windowing](https://web.dev/articles/cls#what_is_cls). [Learn how to improve CLS](https://web.dev/articles/optimize-cls)

Evidence
{
  "displayValue": "5 layout shifts found",
  "description": "These are the largest layout shifts observed on the page. Each table item represents a single layout shift, and shows the element that shifted the most. Below each item are possible root causes that led to the layout shift. Some of these layout shifts may not be included in the CLS metric value due to [windowing](https://web.dev/articles/cls#what_is_cls). [Learn how to improve CLS](https://web.dev/articles/optimize-cls)"
}

PerformancePerformanceBrowser audit

Layout shift culprits

50 Fail

Check name

Layout shift culprits

Score

0/100

Status

fail

Device

desktop

Category

Performance

Fix guidance

Layout shifts occur when elements move absent any user interaction. [Investigate the causes of layout shifts](https://developer.chrome.com/docs/performance/insights/cls-culprit), such as elements being added, removed, or their fonts changing as the page loads.

Evidence
{
  "description": "Layout shifts occur when elements move absent any user interaction. [Investigate the causes of layout shifts](https://developer.chrome.com/docs/performance/insights/cls-culprit), such as elements being added, removed, or their fonts changing as the page loads."
}

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Score history

Public scan score over time

Public reports for this website origin. Select any point or report link to open that canonical report.

1 reports
Public score history report links
Scan dateScoreReadinessReport
59/100Level 3, Bot-AwareCurrent report