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June 4, 2026 · Reference post · Web surface

The 131+ DST factors that make or break a website's agentic readiness

Every audit Appkitekt AI runs on a website rolls up to one score on one frame: Discovery · Selection · Trust. Below is a preview of the full list — only a subset of the 131 factors we score across metadata, per-agent crawl access, RAG retrievability, entity presence and trust signals. Run an audit to unlock every detail.

Why DST for websites

A score is only useful if it tells you where you're losing. DST gives every website factor a home in one of three places an agent's decision can break:

  • Discovery (30%) — can the agent crawl, parse, and retrieve your site at all? Schema markup, llms.txt, per-agent robots rules, sitemap hygiene, entity presence in training data and grounding surfaces.
  • Selection (45%) — once you're in the consideration set, do you get cited? API and tool clarity, decision-grade data, performance, intent alignment, brand preference in prompt testing.
  • Trust (25%) — will the agent stake its answer on you? Authoritativeness, safety and compliance, sentiment, semantic consistency between site and API.

Web · 131 factors

Web surface — DST factor preview

What agents read on your marketing site, docs, schema, llms.txt and grounding surfaces across ChatGPT, Claude, Gemini, Copilot, Perplexity, Grok and Meta AI.

Discovery · weight 30% · 64 factors

Is the app visible to the model's training data and real-time retrieval (RAG)?

Technical Metadata (SEO for Agents) · 16

  • Schema.org implementation (SoftwareApplication, Product, Service)
  • JSON-LD presence and syntax validity
  • OpenGraph (OG) tags for visual model previews
  • Twitter Card metadata (twitter:app:id)
  • Robots.txt allow status for GPTBot, CCBot, PerplexityBot
  • /.well-known/ai-plugin.json or apple-app-site-association
  • XML sitemap reachable at /sitemap.xml, lists all indexable routes, references API docs

+ 9 factors hidden

LLM Training Presence · 8

  • Mention frequency in Common Crawl datasets
  • Brand presence in Wikipedia (entity establishment)
  • Backlinks from high-authority .edu and .gov sites
  • Discussion density on Reddit

+ 4 factors hidden

Contextual & RAG Discovery · 20

  • Semantic density of intent keywords
  • Long-tail problem-solution phrasing in FAQs
  • Regional availability data in metadata
  • Pricing transparency in text (not images)
  • Multi-language metadata
  • Zero-shot brand recognition
  • Few-shot brand recognition
  • Presence in 'Best of [Category]' curated lists

+ 12 factors hidden

Per-Agent Crawl & Retrieval Access · 12

  • Robots.txt explicitly allows GPTBot (ChatGPT training crawler)
  • Robots.txt explicitly allows OAI-SearchBot (ChatGPT live search retrieval)
  • Robots.txt explicitly allows ClaudeBot and Claude-Web (Anthropic crawlers)
  • Robots.txt explicitly allows Google-Extended (Gemini training opt-in)
  • Robots.txt allows Googlebot for Gemini grounded answers (separate from Google-Extended)

+ 7 factors hidden

Per-Agent Social & Grounding Surfaces · 8

  • Verified X / Twitter handle with consistent bio — primary grounding surface for Grok
  • Facebook Page + Instagram Business account + WhatsApp Business — Meta AI grounding surfaces
  • Threads handle linked to the Instagram Business account (Meta AI cross-surface)
  • LinkedIn Company Page complete with verified domain — primary B2B surface for Copilot

+ 4 factors hidden

36 factors in this section are only visible in a full ARO audit.

Run audit to unlock

Selection · weight 45% · 37 factors

When an agent finds 5 options, why does it pick yours?

API & Tool Clarity · 8

  • OpenAPI / Swagger documentation completeness
  • Semantic clarity of function names
  • Precision of parameter descriptions
  • Use of required vs. optional parameters

+ 4 factors hidden

Decision-Making Data · 8

  • Real-time availability indicators
  • Dynamic pricing access via API
  • Shipping speed/estimates as raw data
  • Discount/coupon code accessibility

+ 4 factors hidden

Performance & Efficiency · 9

  • API latency (Time to First Byte)
  • Token efficiency (minimalist JSON payloads)
  • Support for batch requests
  • Rate limit transparency

+ 5 factors hidden

User Intent Alignment · 12

  • Brand preference in prompt testing
  • Cost-effectiveness perception (value vs premium)
  • Niche specialization (generalist vs expert)
  • Response relevance to the problem statement
  • Historical selection rate (winner's circle)

+ 7 factors hidden

20 factors in this section are only visible in a full ARO audit.

Run audit to unlock

Trust · weight 25% · 30 factors

Does the agent believe the info is accurate, safe, and authoritative?

Authoritativeness & Verification · 8

  • Verified badges on social/business directories
  • WHOIS data transparency
  • Physical address verification
  • Customer support response time metrics

+ 4 factors hidden

Safety & Compliance · 7

  • Privacy policy clarity (GDPR/CCPA)
  • OWASP Top 10 compliance for LLM apps
  • Prompt injection guardrails

+ 4 factors hidden

Reputation & Sentiment · 7

  • Sentiment score on Reddit/forums
  • Ratio of verified-purchase reviews
  • Public security bug bounty program

+ 4 factors hidden

Semantic Consistency · 8

  • Information parity (website vs API)
  • Uniformity of brand voice across LLMs
  • Fact-check pass rate
  • Lack of conflicting metadata

+ 4 factors hidden

16 factors in this section are only visible in a full ARO audit.

Run audit to unlock

Next step

Unlock the complete factor list.

Run an ARO audit to see every signal scored for your website.

Run audit