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SCAN HISTORY
30/100 Compare
30/100 Compare
34/100 Compare
37/100 Compare
Changes since selected scan Score change: 0

Resolved

  • None

New issues

  • None

Category changes

  • None

Result summary

Readiness profiles

Methodology 2026-08-29

Measured stable-core coverage

30/100

Methodology grade

D

38 core checkpoints assessed

13

Passed

1

Partial

24

Failed

11

Skipped

Strongest category

AI Content Discovery

Weakest category

Agent Protocols

Action plan

Priority actions Highest-impact implementation details
3 prioritized actions

Prioritized by exact impact on the overall stable-core score.

Failed OpenAPI / API documentation +15 overall pts

No OpenAPI or Swagger documentation found.

OpenAPI / API documentation
HIGH

OpenAPI specifications let AI agents understand and call your API programmatically. AI coding assistants and agent frameworks use OpenAPI to generate correct API calls automatically.

Create an OpenAPI 3.x specification and serve it at /openapi.json or /.well-known/openapi to enable AI agents to discover and use your API.

openapi.json json 
{
  "openapi": "3.1.0",
  "info": {
    "title": "My API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/search": {
      "get": {
        "summary": "Search items",
        "parameters": [
          {"name": "q", "in": "query", "schema": {"type": "string"}}
        ]
      }
    }
  }
}
Sources
Failed JSON-LD present +5 overall pts

No valid JSON-LD blocks with schema.org @context found.

JSON-LD present
HIGH

JSON-LD is the preferred format for structured data by Google and AI search engines. It tells AI systems exactly what your page is about using a standardized vocabulary.

Add at least one <script type="application/ld+json"> block with "@context": "schema.org" describing your organization or page content. This gives agents an unambiguous, machine-readable description of your page and makes it eligible for rich results in search.

JSON-LD html 
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://tribalwars.nl",
  "logo": "https://tribalwars.nl/logo.png"
}
</script>
Sources
Failed High-value schema types +5 overall pts

No high-value schema types found. We check for 17 recognized types including Article, Product, SoftwareApplication, FAQPage, LocalBusiness, VideoObject, and more.

High-value schema types
HIGH

Certain schema types (Article, Product, FAQPage, etc.) trigger rich results in Google and Bing and give agents typed, unambiguous entities to extract instead of inferring from prose. Their effect on AI-search citations is indirect, via the search indexes that feed products like ChatGPT and Perplexity.

Add JSON-LD markup for content-appropriate types like Article, Product, SoftwareApplication, FAQPage, LocalBusiness, Service, Event, or VideoObject so agents and search engines can identify your content type and extract structured facts reliably.

JSON-LD html 
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Your App Name",
  "operatingSystem": "Web",
  "applicationCategory": "BusinessApplication",
  "offers": {
    "@type": "Offer",
    "price": "0",
    "priceCurrency": "USD"
  }
}
</script>
Sources
Fix with AI Skills
$ /plugin marketplace add bartwaardenburg/isagentready-skills

Detailed results

Agent Protocols Weight 15% Needs attention

1 failed score-impacting checkpoint

5 bonus opportunities and 3 informational findings; do not affect the core score

Core score 0/100
AI Content Discovery Weight 30% Needs attention

3 failed, 1 partial score-impacting checkpoints

6 bonus opportunities; do not affect the core score

Core score 58/100
Security & Trust Weight 15% Needs attention

7 failed score-impacting checkpoints

1 bonus opportunity; does not affect the core score

Core score 21/100
Content & Semantics Weight 20% Needs attention

8 failed score-impacting checkpoints

Core score 47/100
AI Search Signals Weight 20% Needs attention

5 failed score-impacting checkpoints

Core score 0/100
AI Training Exposure Supplemental

Does not affect the readiness score

No AI training protections detected. Your content may be freely used for AI model training.

Common Crawl presence Unknown

Could not determine the latest Common Crawl index.

Training crawler blocking Not found

No training crawlers are blocked in robots.txt. All known AI training bots can access your content.

TDMRep declaration Not found

No TDMRep file found at /.well-known/tdmrep.json. The TDM Reservation Protocol (W3C) lets you declare whether you reserve text and data mining rights. See w3.org/community/reports/tdmrep/CG-FINAL-tdmrep-20240510 for the specification.

ai.txt policy Not found

No ai.txt file found. ai.txt lets you declare AI usage preferences for your content.

Web Bot Auth Not found

No Web Bot Auth signature key directory found. Bots cannot prove their identity to origins via signed HTTP requests.

Developer Tools

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SCAN
claude mcp add isagentready-mcp -- npx -y isagentready-mcp
FIX
/plugin marketplace add bartwaardenburg/isagentready-skills
MCP Server AI Skills
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