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58/100

OVERALL SCORE

Level 3, Bot-Aware

Moderate readiness for AI agents
AIDiscoverability44%Agent Easeof Use55%Security& Trust76%GEO, AIO, AEO62%SEO92%Performance56%Accessibility93%
  • AI Discoverability 44 out of 100
  • Agent Ease of Use 55 out of 100
  • Security & Trust 76 out of 100
  • GEO, AIO and AEO 62 out of 100
  • SEO 92 out of 100
  • Performance 56 out of 100
  • Accessibility 93 out of 100

CAPTURED SCREENSHOT

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What AI sees of your website

The London School of Economics and Political Science - LSE favicon

The London School of Economics and Political Science - LSE

LSE is a world-leading social science specialist university, awarded University of the Year 2025 and ranked 1st in London and the UK in 2025 and 2026.

Next step

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Detailed report scores grouped by capability area
MetricScoreStatusPassedFailedWarningEvidence
AI Discoverability
44
Priority fix1952View details
Discoverability
63
Needs work700
Content Readiness
25
Priority fix1142View details
Bot Access Control
45
Priority fix110View details
Agent Ease of Use
55
Needs work200
API
67
Needs work100
Skill Discovery
54
Needs work100
GEO, AIO and AEO
62
Needs work900
GEO Readiness
Not Applicable
Not Applicable300
AIO Readiness
Not Applicable
Not Applicable300
AEO Readiness
Not Applicable
Not Applicable300
SEO
92
Strong800
SEO
92
Strong800
Security & Trust
76
Mostly ready1800
Security & Trust
76
Mostly ready1800
Performance
56
Needs work1300
Performance
56
Needs work1300

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.

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.

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

AI DiscoverabilityContent ReadinessEstablished

Content freshness signals

Content freshness signals is missing or incomplete.

50 Fail

Needs attention

Content freshness signals

Failed check
01

Issue

Content freshness signals are incomplete: missing any valid freshness date in Last-Modified, Schema.org, Open Graph, Dublin Core, generic meta, or sitemap lastmod.

Details

02

Why it matters

Freshness signals help agents, crawlers, and search systems decide whether content is current enough to cite, summarize, cache, or compare against newer sources.

Check name

Content freshness signals

Score

0/100

Status

fail

Category

Content Readiness

Maturity

Established

Goal

Expose modified and published dates for freshness-aware retrieval, citation, and ranking.

Result

Content freshness signals is missing or incomplete.

Validation steps

  1. Validate Last-Modified header

    No valid Last-Modified HTTP header was found.

  2. Validate structured freshness dates

    No Schema.org freshness dates were found.

  3. Validate metadata freshness dates

    No Open Graph, Dublin Core, or generic meta freshness date was found.

  4. Corroborate with sitemap lastmod

    Add a sitemap entry with a valid lastmod for the canonical page URL when sitemap corroboration is useful.

Evidence log4 steps · 16 lines
Validate Last-Modified header [fail]! No valid Last-Modified HTTP header was found.INFOValidate Last-Modified headerINFOReading Last-Modified response headerFAILCheck Last-Modified header is present and parseable actual="missing" expected="valid" alternateDates=[]FAILLast-Modified header is missing or invalidValidate structured freshness dates [fail]! No Schema.org freshness dates were found.INFOValidate structured freshness datesINFOCollecting Schema.org freshness dates from JSON-LD, Microdata, and RDFaFAILCheck structured freshness date count actual=0 expected="> 0" invalidDateCount=0 formats={} alternateDates=[]FAILNo structured freshness dates foundValidate metadata freshness dates [fail]! No Open Graph, Dublin Core, or generic meta freshness date was found.INFOValidate metadata freshness datesINFOCollecting Open Graph, Dublin Core, and generic meta freshness datesFAILCheck metadata freshness date count actual=0 expected="> 0" metaDateCount=0 invalidDateCount=0 alternateDates=[]FAILNo metadata freshness dates foundCorroborate with sitemap lastmod [warning]INFOCorroborate with sitemap lastmodINFODiscovering sitemap candidates and matching the scanned page URL candidateCount=1 attempts=1WARNCheck matching sitemap lastmod actual="no match" expected="valid match when available" robotsStatusCode=200WARNNo matching sitemap lastmod found after sitemap attempts attempts=1

AI DiscoverabilityContent ReadinessEstablished

Author attribution

Author attribution is partially implemented.

22 Warning

Needs attention

Author attribution

Warning
01

Issue

No named author or publisher identity could be extracted.

02

Why it matters

Author attribution helps agents cite content responsibly, assess source credibility, and distinguish editorial pages from anonymous marketing copy.

Check name

Author attribution

Score

55/100

Status

warning

Category

Content Readiness

Maturity

Established

Goal

Identify content authors or publishers for trust and attribution.

Result

Author attribution is partially implemented.

Validation steps

  1. Schema.org attribution

    Schema.org attribution is incomplete or relies only on publisher/fallback evidence.

  2. Author identity quality

    No named author or publisher identity could be extracted.

Evidence log2 steps · 8 lines
Schema.org attribution [warning]! Schema.org attribution is incomplete or relies only on publisher/fallback evidence.INFOSchema.org attributionINFOChecking structured data for author, creator, and publisher contributorsWARNCheck named Schema.org author count actual=0 expected="> 0" authorCount=0 publisherCount=0 namedContributors=0 authors=[] publishers=[] formats=[]WARNSchema.org attribution is incomplete or fallback-only authorCount=0 publisherCount=0 authors=[] publishers=[]Author identity quality [fail]! No named author or publisher identity could be extracted.INFOAuthor identity qualityINFOChecking contributors for stable identity signalsFAILCheck identified contributor count actual=0 expected="> 0" namedContributors=0 identifiedContributors=[] unidentifiedContributors=[]FAILNo named contributor identity could be extracted

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Score history

Public scan score over time

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1 reports
Public score history report links
Scan dateScoreReadinessReport
58/100Level 3, Bot-AwareCurrent report