CanAgentUse tools

UCP Suite

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

MCP Playground

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

A2A Playground

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

Agent Website Viewer

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

SCANNED
Jun 19, 2026, 6:05 AM
VISIBILITY
Public
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60/100

OVERALL SCORE

Level 3, Bot-Aware

Moderate readiness for AI agents
AIDiscoverability43%Agent Easeof Use57%Security& Trust83%GEO, AIO, AEO64%SEO100%Performance98%Accessibility34%
  • AI Discoverability 43 out of 100
  • Agent Ease of Use 57 out of 100
  • Security & Trust 83 out of 100
  • GEO, AIO and AEO 64 out of 100
  • SEO 100 out of 100
  • Performance 98 out of 100
  • Accessibility 34 out of 100

CAPTURED SCREENSHOT

Captured website desktop screenshot

What AI sees of your website

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Free and Open source tool to streamline document filling and signing. Create custom PDF forms to complete and sign with an easy to use online tool. Automatic digital signature.

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Detailed report scores grouped by capability area
MetricScoreStatusPassedFailedWarningEvidence
AI Discoverability
43
Priority fix1522View details
Discoverability
67
Needs work800
Content Readiness
15
Priority fix500
Bot Access Control
46
Priority fix222View details
Agent Ease of Use
57
Needs work700
API
67
Needs work200
Skill Discovery
60
Needs work500
GEO, AIO and AEO
64
Needs work900
GEO Readiness
Not Applicable
Not Applicable300
AIO Readiness
Not Applicable
Not Applicable300
AEO Readiness
Not Applicable
Not Applicable300
SEO
100
Strong1000
SEO
100
Strong1000
Security & Trust
83
Mostly ready2010View details
Security & Trust
83
Mostly ready2010View details
Performance
98
Strong2000
Performance
98
Strong2000

Prioritized recommendations

Issues ranked by score impact

3 items need attention

Security & TrustSecurity & TrustEstablished

Content-Security-Policy

Content-Security-Policy failed at "Find enforcing CSP delivery".

60 Fail

Needs attention

Content-Security-Policy

Failed check
01

Issue

Applicable HTML response is missing an enforcing Content-Security-Policy header.

02

Why it matters

Content Security Policy reduces the impact of injection bugs by limiting where scripts, styles, frames, forms, and other browser resources can load or execute.

Check name

Content-Security-Policy

Score

40/100

Status

fail

Category

Security & Trust

Maturity

Established

Goal

Constrain browser resource loading and script execution with an enforcing Content-Security-Policy header.

Result

Content-Security-Policy failed at "Find enforcing CSP delivery".

Validation steps

  1. Find enforcing CSP delivery

    Applicable HTML response is missing an enforcing Content-Security-Policy header.

Evidence log1 step · 4 lines
Find enforcing CSP delivery [fail]! Applicable HTML response is missing an enforcing Content-Security-Policy header.INFOFind enforcing CSP deliveryINFORead CSP delivery headers enforcingHeader="missing" reportOnlyHeader="missing" metaPolicyCount=0 legacyHeadersPresent=[]FAILRequire enforcing Content-Security-Policy header actual="missing" expected="present" issue="Applicable HTML response is missing an enforcing Content-Security-Policy header."FAILApplicable HTML response is missing an enforcing Content-Security-Policy header.

AI DiscoverabilityBot Access ControlEstablished

AI bot rules in robots.txt

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

35 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 DiscoverabilityBot Access ControlEmerging recommendation

ai.txt policy

ai.txt policy failed at "Fetch /ai.txt".

25 Fail

Needs attention

ai.txt policy

Failed check
01

Issue

/ai.txt returned HTTP 500.

02

Why it matters

ai.txt is a fragmented emerging convention. It can communicate human-readable AI crawling, training, attribution, restriction, and contact guidance, but it is not a standard access-control mechanism and absence should not be penalized.

Check name

ai.txt policy

Score

50/100

Status

fail

Category

Bot Access Control

Maturity

Emerging recommendation

Goal

Publish an advisory human-readable AI usage policy only when the site intentionally needs one.

Result

ai.txt policy failed at "Fetch /ai.txt".

Validation steps

  1. Fetch /ai.txt

    /ai.txt returned HTTP 500.

  2. Parse ai.txt policy

    ai.txt is present but does not follow the AI Visibility section model.

  3. Validate policy content

    ai.txt does not follow the AI Visibility section model; treating it as non-standard advisory text.

Evidence log3 steps · 14 lines
Fetch /ai.txt [fail]! /ai.txt returned HTTP 500.INFOFetch /ai.txtINFORequesting optional advisory policy file at /ai.txtFAILCompare /ai.txt HTTP response actual=500 expected="2xx when ai.txt is intentionally published; 404/410 means absent optional file" contentType="text/plain; charset=utf-8" length=182FAIL/ai.txt returned HTTP 500. statusCode=500Parse ai.txt policy [warning]! ai.txt is present but does not follow the AI Visibility section model.INFOParse ai.txt policyINFODetecting ai.txt convention from bracket sections, frontmatter, headings, and ai.txt context linksINFODetected policy structure convention="unknown-text" sections=[] markdownHeadings=[]WARNCheck AI Visibility required sections actual="missing identity, permissions, restrictions" expected="identity, permissions, and restrictions" missingRecommended=["attribution","contact","content-types"]WARNai.txt is present but does not follow the AI Visibility section model.Validate policy content [warning]! ai.txt does not follow the AI Visibility section model; treating it as non-standard advisory text.INFOValidate policy contentINFOChecking required section content, permission/restriction language, attribution, contact details, and safety risks convention="unknown-text"INFODetected policy signals hasPermissionLanguage=false hasRestrictionLanguage=false hasTrainingLanguage=false hasAttributionLanguage=false hasContact=falseWARNCheck required and recommended section coverage actual={"missingRequired":["identity","permissions","restrictions"],"missingRecommended":["attribution","contact","content-types"]} expected={"missingRequired":[],"recommendedPresentWhenPossible":true}WARNai.txt does not follow the AI Visibility section model; treating it as non-standard advisory text.

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Score history