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.animalz.co/
SCANNED
Jul 6, 2026, 5:28 AM
VISIBILITY
Public
SUITE2026.06.10
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54/100

OVERALL SCORE

Level 3, Bot-Aware

Moderate readiness for AI agents
AIDiscoverability43%Agent Easeof Use53%Security& Trust62%GEO, AIO, AEO56%SEO92%Performance78%Accessibility53%
  • AI Discoverability 43 out of 100
  • Agent Ease of Use 53 out of 100
  • Security & Trust 62 out of 100
  • GEO, AIO and AEO 56 out of 100
  • SEO 92 out of 100
  • Performance 78 out of 100
  • Accessibility 53 out of 100

CAPTURED SCREENSHOT

Captured website desktop screenshot

What AI sees of your website

Animalz | Content Marketing Services for SaaS Companies favicon

Animalz | Content Marketing Services for SaaS Companies

Animalz is a content marketing agency that provides content strategy and creation to B2B SaaS companies, venture capitalists, and other tech companies.

Open Agent View

Next step

Turn this report into a fix workflow

2 failed checks are ready to move into MCP or CLI remediation. Generate a repair prompt, connect the scanner to your coding agent, or open the integration docs before your next rescan.

Fix with MCP / CLI
Detailed report scores grouped by capability area
MetricScoreStatusPassedFailedWarningEvidence
AI Discoverability
43
Priority fix1410View details
Discoverability
63
Needs work700
Content Readiness
19
Priority fix600
Bot Access Control
45
Priority fix110View details
Agent Ease of Use
53
Needs work1121View details
Auth
62
Needs work1011View details
Google Agentic Browsing
50
Needs work110View details
GEO, AIO and AEO
56
Needs work800
GEO Readiness
Not Applicable
Not Applicable200
AIO Readiness
Not Applicable
Not Applicable300
AEO Readiness
Not Applicable
Not Applicable300
SEO
92
Strong900
SEO
92
Strong900
Security & Trust
62
Needs work1300
Security & Trust
62
Needs work1300
Performance
78
Mostly ready1500
Performance
78
Mostly ready1500

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

Agent Ease of UseAuthEmerging recommendation

Auth.md Agent Registration

Auth.md Agent Registration failed at "Fetch and validate /auth.md".

52 Fail

Needs attention

Auth.md Agent Registration

Failed check
01

Issue

auth.md could not be fetched.

Details

02

Why it matters

Human login and signup flows are often opaque to agents. Auth.md gives automated clients a stable registration contract instead of forcing them to scrape docs, automate browser forms, or guess credential flows.

Check name

Auth.md Agent Registration

Score

48/100

Status

fail

Category

Auth

Maturity

Emerging recommendation

Goal

Publish Auth.md v1 metadata so agents can discover how to register, claim a user, and obtain credentials.

Result

Auth.md Agent Registration failed at "Fetch and validate /auth.md".

Validation steps

  1. Fetch and validate /auth.md

    auth.md could not be fetched.

    /auth.md is missing or not usable as agent registration guidance

  2. Validate Auth.md authorization metadata

    OAuth authorization-server metadata did not include usable Auth.md v1 fields. agent_registration_endpoint issues: [{"field":"agent_registration_endpoint","issue":"Expected an absolute HTTPS URL."}]; missing credential_types_supported.

    Authorization-server metadata lacks Auth.md v1 fields
Evidence log2 steps · 13 lines
Fetch and validate /auth.md [fail]! auth.md could not be fetched.INFOFetch and validate /auth.mdINFOFetch Auth.md-related resource path="/auth.md" statusCode=404 contentType="text/html; charset=utf-8" bytes=43741FAILCompare response Content-Type with expected Auth.md media type actual=false expected=trueFAILCompare Auth.md/OAuth metadata validation result actual=false expected=trueFAILAuth.md validation issue issue="auth.md could not be fetched."FAILauth.md could not be fetched.Validate Auth.md authorization metadata [warning]! OAuth authorization-server metadata did not include usable Auth.md v1 fields. agent_registration_endpoint issues: [{"field":"agent_registration_endpoint","issue":"Expected an absolute HTTPS URL."}]; missing credential_types_supported.INFOValidate Auth.md authorization metadataINFOFetch Auth.md-related resource path="/.well-known/oauth-authorization-server" statusCode=200 contentType="application/json" bytes=907WARNCompare response Content-Type with expected Auth.md media type actual=true expected=trueWARNCompare Auth.md/OAuth metadata validation result actual=false expected=trueWARNCompare supported credential type count actual=0 expected="> 0"WARNAuth.md validation issue issue="OAuth authorization-server metadata did not include usable Auth.md v1 fields. agent_registration_endpoint issues: [{\"field\":\"agent_registration_endpoint\",\"issue\":\"Expected an absolute HTTPS URL.\"}]; missing credential_types_supported."WARNOAuth authorization-server metadata did not include usable Auth.md v1 fields. agent_registration_endpoint issues: [{"field":"agent_registration_endpoint","issue":"Expected an absolute HTTPS URL."}]; missing credential_types_supported.

Agent Ease of UseGoogle Agentic BrowsingBrowser audit

Accessibility tree is not well-formed

100 Fail

Check name

Accessibility tree is not well-formed

Score

0/100

Status

fail

Device

desktop

Category

Google Agentic Browsing

Fix guidance

A well-formed [accessibility tree](http://goo.gle/lighthouse-agentic-a11y) helps AI agents to navigate and interact with the page.

Evidence
{
  "description": "A well-formed [accessibility tree](http://goo.gle/lighthouse-agentic-a11y) helps AI agents to navigate and interact with the page."
}

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Fix with MCP or CLI

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Fix with MCP / CLI

Score history

Public scan score over time

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

2 reports
Public score history report links
Scan dateScoreReadinessReport
48/100Level 2, Agent-LimitedView report
54/100Level 3, Bot-AwareCurrent report