Public machine-readable hub
Last updated May 28, 2026 · Kristina Shrider · ORCID 0009-0002-2655-4629
Market Disruptors AI Visibility Agency publishes these files so crawlers, agents, and research tools can inspect our business identity, services, author entity, prompt targets, framework pages, DOI-backed methodology, and source records.
The files do not guarantee citations. They reduce ambiguity and point machines back to visible Market Disruptors AI Visibility Agency pages, including our AI visibility methodology, testing log, and Kristina Shrider author profile.
Validation rules
Customer-domain URLs only
No fake reviews endpoint
No empty endpoint stubs
No vendor-domain entity IDs
No dealer or inventory template fields
Public discovery files are crawlable
Private API routes stay protected
Machine files point back to visible Market Disruptors AI Visibility Agency pages
This is the public index for Market Disruptors AI Visibility Agency's AI discovery layer. If a crawler or researcher wants the shortest path to our structured business facts, author identity, services, site graph, prompt registry, and evidence records, this page points to the current resources.
The page is written for both humans and machines. Each section gives a short answer first, then points to the file or page that verifies the claim. That format is intentional: AI systems need extractable facts, and buyers need a clear audit trail.
These short answer blocks define the page in extractable language before the longer resource list.
AI discovery files give crawlers and AI agents a concise map of verified business facts, canonical pages, author identity, services, framework definitions, public APIs, and source records. They reduce ambiguity, but they do not guarantee that any model will cite the site.
The ai.marketdisruptorsagency.com subdomain is a clean machine-readable entry point. It mirrors public discovery records while canonical authority stays on marketdisruptorsagency.com, where the visible pages, schema, internal links, and conversion paths live.
Humans should start with the visible methodology and framework pages, then use the JSON files as supporting records. The strongest path is page content first, schema second, discovery files third, and third-party proof as the authority layer.
The `ai.` subdomain is the clean machine endpoint. The same resources also remain available on the main domain so public links and crawlers have a fallback path.
Site graph for pages, services, frameworks, prompts, evidence, and trust metadata.
Manifest pointing agents to Market Disruptors AI Visibility Agency business, service, prompt, author, and evidence resources.
OpenAPI contract for public Market Disruptors AI Visibility Agency discovery endpoints.
Plugin-style compatibility manifest for systems that inspect this older discovery format.
Short human-readable map of Market Disruptors AI Visibility Agency's priority pages and framework definitions.
Canonical formal methodology package for MAHI Index™, MAD-M™, and MAHI-100.
Public source repository for the AI Citation Visibility Framework v0.2.2 release.
These endpoints return JSON. They are public support files for inspection, not lead forms or private client data.
Verified business identity, contact, service area, founder, and sameAs signals.
Structured service catalog mapped to canonical Market Disruptors AI Visibility Agency service pages.
Priority page index for agency, framework, proof, and conversion pages.
Prompt-aligned answer surfaces mapped to canonical pages.
Kristina Shrider author identity with ORCID-backed sameAs references.
Source records that support Market Disruptors AI Visibility Agency's AI visibility claims and public testing log.
AI discovery files are not a shortcut around content quality. They help organize the facts that already appear on the public website: author identity, services, framework definitions, source records, and canonical pages.
We still prioritize visible pages, primary sources, answer-ready copy, clean schema, crawl access, third-party corroboration, and first-party measurement.
The business, founder, services, and frameworks are connected through stable URLs and schema IDs.
High-intent questions point to the best Market Disruptors AI Visibility Agency landing pages instead of leaving systems to guess.
Source records and the testing log help separate measured claims from unsupported claims.
The files have validation rules so weak records, empty stubs, and fake review signals do not go live.
Different AI systems inspect and cite sources differently. This page keeps the same canonical facts, but it makes the discovery layer readable for multiple retrieval patterns.
For ChatGPT and Claude-style retrieval, the page emphasizes explicit entity labels, author identity, DOI-backed methodology, and stable source URLs. These systems need enough context to separate Market Disruptors AI Visibility Agency from similarly named entities.
For Perplexity and Bing Copilot-style answers, the page prioritizes crawlable endpoints, source records, visible dates, and concise answer blocks. These systems often reward pages that make source selection and citation context easier to inspect.
For Google AI surfaces, the discovery files are only support assets. The primary work remains useful visible content, crawlable pages, internal linking, structured data that matches the page, and business information that users can verify.
For agentic systems, this page connects the business, founder, services, frameworks, and methodology package through stable URLs. The goal is not secret optimization; it is reducing entity confusion when a system compares sources.
They are public machine-readable support files that describe Market Disruptors AI Visibility Agency, Kristina Shrider, services, framework pages, prompt targets, DOI-backed methodology, and evidence records. They support inspection. They do not replace visible pages.
No. They make Market Disruptors AI Visibility Agency easier to inspect, verify, and connect to canonical pages. They do not force ChatGPT, Perplexity, Google AI, Gemini, or Copilot to cite the site.
The subdomain gives crawlers and agents a clean machine-readable entry point while keeping all entity authority on the Market Disruptors AI Visibility Agency domain.
They are public support files linked from Market Disruptors AI Visibility Agency's AI discovery hub, llms.txt, robots.txt, and site graph. They are crawlable so machines can inspect the records and connect them back to visible canonical pages.
No. AI discovery files support retrieval, inspection, and entity disambiguation. They do not replace public pages, external proof, reviews, citations, backlinks, or customer trust signals.
We are watching whether the AI discovery layer changes crawl patterns, prompt mentions, Bing AI Performance citation activity, and entity accuracy for Market Disruptors AI Visibility Agency. Results will be logged on /whats-next.