AI Visibility: Technology, Standards & Implementation

This article is written for developers, SEO experts, and technically interested studio operators. It explains which standards and processes are used on fragfitty.de so that studio data remains discoverable, understandable, and up to date in AI systems.

What is AI visibility?

AI visibility means that a studio is mentioned more visibly and more consistently in answers from systems such as ChatGPT, Gemini, Claude, Copilot, or Perplexity. To make that possible, content must be provided in machine-readable, standardized formats.

fragfitty.de handles this preparation automatically for studios with a Plus or Premium subscription.

In a marketing context, this corresponds to AEO (Answer Engine Optimization): similar to SEO in its early years, early optimization can create a lasting advantage.

AI Profile (from Plus)

For studios, this means in one sentence: AI Profile: your studio is found more easily in 30+ AI systems.

For every studio from Plus upward, an AI Profile is generated under /gym/{studio-slug}/. It bundles all relevant data in formats that crawlers, search engines, and LLMs can process directly.

AI Profile	File	Description
AI description	llms.txt, llms-full.txt	Machine-readable description in the llmstxt.org format
Structured data	structured-data.json	Schema.org JSON-LD (type: HealthClub) for search engines and AI systems
Profile page	index.md	Studio profile as Markdown for AI crawlers
Full profile data	(inline in the AI files)	Complete admin data set including rates, additional services, team, FAQs, news, videos, and reviews
Metadata	(inline)	AI meta tags, Schema.org JSON-LD, and AI tag in the HTML of the studio page

The files are updated daily by the sitemap generator and signaled through the sitemap with changefreq: daily.

AI News (Premium)

For studios, this means in one sentence: AI News automatically turns social posts into news for AI systems.

Premium studios can connect Facebook, Instagram, TikTok, and YouTube. New content is imported manually or automatically every day.

Fitty detects relevant updates such as offers, events, new classes, changed opening hours, or new services and turns them into structured news.

These news items appear on the studio page and in the AI files. This makes current studio updates easier for AI systems and search engines to read.

Step	Detail
Source	Facebook, Instagram, TikTok, YouTube
Sync	Manual or automatic daily sync
Detection	Relevant updates are detected and prepared as news
Output	News on the studio page and in the AI files

AI Push (Premium)

For studios, this means in one sentence: AI Push: changes are submitted immediately to 30+ AI and search systems.

Premium studios receive active indexing. When relevant profile changes occur, fragfitty.de submits updates directly to supported search and AI systems instead of relying only on the next regular crawl. This means we actively handle the technical submission immediately. When an external service processes or recrawls the change is still controlled by the respective provider.

Service	Submission	Description
OpenAI ChatGPT	Bing Content Submission API	ChatGPT Search uses the Bing index as an important data source
Google Gemini	Google Indexing API	Direct technical submission to Google systems
Microsoft Copilot	Bing Content Submission API	Copilot uses Bing data for grounding
IndexNow	IndexNow protocol	Ping to additional search systems, including Bing, Yandex, and Naver

AI Chat (Premium)

Premium studios also receive an AI Chat. It appears on the studio profile page and can be embedded into the studio's own website. Visitors receive direct answers about prices, opening hours, equipment, and services.

How it works

The AI Chat uses the current studio data set from the database as its primary knowledge base (grounding) and therefore works with live data instead of a static export. The public AI files (llms-full.txt/llms.txt + structured-data.json) remain relevant for external AI crawlers and platforms, but they are no longer the primary internal chat source. Optionally, up to 5 custom documents (PDF, Markdown, text) can be added as additional context.

Property	Detail
LLM	Configurable chat model with grounded answers
Streaming	Server-Sent Events (SSE) for token-by-token output
Context	Live studio database + uploaded documents (max. 50,000 characters), supplemented by public AI files for external AI systems
Rate limiting	500 messages/IP/24h, 2,000/studio/24h, 200/session
Embed	`<script>` tag with Shadow DOM, authenticated via embed token

Embed on the studio website

Studio operators receive an embed code in the dashboard:

<script src="https://fragfitty.de/embed/agent.js?token=..." async></script>

The script renders an isolated widget in the Shadow DOM and connects to the API. Domain validation ensures that a token can only be used on the registered studio domain.

AI Search

AI Search understands natural language. Users can phrase their request freely, for example "Affordable gym with sauna in Berlin", and the LLM translates this input into structured filters.

Property	Detail
Input	Free text in natural language
Processing	LLM extracts city, radius, price limit, and features
Result	Matching studios as a card carousel in chat
Refinement	Interactive filter pills (radius, price, equipment) without another LLM call
Handoff	"Frag Fitty" button transfers active filters into the classic results view

This improves matching quality, especially for complex search queries with several criteria.

Platform Infrastructure

In addition to studio-specific files, there are central entry points at platform level.

Core files

File	Purpose	Link
llms.txt	Short platform overview for LLMs	/llms.txt
llms-full.txt	Extended version with example studios	/llms-full.txt
structured-data.json	Schema.org JSON-LD manifest	/structured-data.json
openapi.yaml	OpenAPI 3.1 documentation	/openapi.yaml
ai.txt	AI crawler metadata (entry points, license, crawl notes)	/ai.txt

AI metadata (`.well-known/ai-metadata/`)

File	Standard	Link
model.jsonld	Schema.org SoftwareApplication	/.well-known/ai-metadata/model.jsonld
webpage.jsonld	Schema.org WebPage	/.well-known/ai-metadata/webpage.jsonld
dataset.croissant.json	Croissant ML data set description	/.well-known/ai-metadata/dataset.croissant.json
dcat.jsonld	W3C DCAT v3 data catalog	/.well-known/ai-metadata/dcat.jsonld

Agent Discovery

Two discovery protocols allow AI agents to automatically detect our capabilities.

MCP Well-Known Discovery

/.well-known/mcp/servers.json follows the Model Context Protocol. MCP-compatible clients such as Claude Desktop, Cursor, or VS Code can detect the search capabilities directly.

A2A Agent Card

/.well-known/agent-card.json implements Google's Agent-to-Agent Protocol. This allows A2A-compatible systems to discover our agent capabilities in a standardized way.

Metadata

Inline LLM script tags

Every page includes a global <script type="text/llms.txt"> tag in the HTML head with platform context. On studio detail pages (from Plus/Premium), an additional studio-specific tag is added. This follows the Vercel proposal for inline LLM instructions.

Browsers ignore the unknown type value; the tags are intended for AI crawlers.

AI meta tags

Every page contains additional meta tags for AI systems:

Meta tag	Example value	Purpose
`ai:content_type`	`local_business_profile`	Page type for AI systems
`ai:summary`	Description text	Short summary of the content
`ai:page_type`	`content_page`	Page classification
`ai:data_freshness`	`2025-06-01`	Data freshness
`ai:target_audience`	`fitness_interested_people`	Target audience
`ai:geographic_focus`	`Berlin`	Geographic focus
`ai:content_category`	`business_profile`	Content category

Dublin Core metadata (dc:language, dc:creator, dc:publisher, dc:date) is also set.

AI resource links

In the HTML head, <link> tags point to central AI resources:

llms.txt
structured-data.json
openapi.yaml
model.jsonld, dataset.croissant.json, webpage.jsonld
dcat.jsonld

On studio detail pages (from Plus), studio-specific AI files are linked as well (llms.txt, llms-full.txt, structured-data.json, index.md).

Schema.org structured data

Every page contains JSON-LD blocks with Schema.org types:

Schema	Pages	Content
`Organization`	all	Platform data, contact, logo
`WebSite`	all	Website description with `SearchAction`
`WebPage`	all	Page metadata including `SpeakableSpecification`
`HealthClub`	Studio detail	Name, address, geo, opening hours, rates, reviews
`FAQPage`	Studio detail	Question-answer pairs
`BreadcrumbList`	Studio, articles	Navigation structure
`CollectionPage`	Search results	List of found studios
`Article`	Articles	Title, publication date

Studio pages also include ReserveAction for trial sessions.

IETF AIPREF Content-Usage

Every HTML response contains this header and meta tag:

Content-Usage: train-ai=y, search=y, ai-input=y

This follows the current IETF AIPREF Working Group draft and signals permitted AI usage in a standardized way.

Compliance & Rights

W3C TDMRep

/.well-known/tdmrep.json implements the W3C TDMRep standard. This signals in an EU-compliant way that text and data mining of the content is permitted.

Cloudflare Content Signals

The robots.txt also includes a content signal:

# Content-Signal: search=yes, ai-train=yes, ai-input=yes

Licenses

All AI-related content is published under CC-BY-4.0 (see ai.txt).

Supported AI Crawlers

The robots.txt allows access for 29+ AI crawlers/user agents.

OpenAI: GPTBot, OAI-SearchBot, ChatGPT-User

Anthropic: ClaudeBot, Claude-SearchBot, Claude-User, Claude-Web, Anthropic-AI

Google: Google-Extended, Google-CloudVertexBot, GoogleAgent-Mariner, Googlebot

Meta: FacebookBot, Meta-ExternalAgent, Meta-ExternalFetcher

Microsoft: Bingbot

Apple: Applebot, Applebot-Extended

Others: PerplexityBot, Perplexity-User, Amazonbot, Bytespider, CCBot, cohere-ai, DeepSeekBot, DuckAssistBot, MistralAI-User, Diffbot, YandexBot

The list is continuously expanded as soon as relevant new systems appear.

SEO Ecosystem

AI visibility is not created by technology alone, but also by a resilient content and SEO foundation.

Editorial content (560+ articles)

An automated content system with 560+ SEO-optimized expert articles runs under /artikel/. Pipeline: keyword research -> external fact checking -> LLM generation -> image generation.

The articles are internally linked with studio, city, and brand pages and include Article Schema.org markup.

Brand comparisons (programmatic SEO)

Automatically generated comparison pages under /vergleich/, for example /vergleich/mcfit-vs-fitx, compare brands using real data points such as average prices, equipment coverage, and city overlap. Each page includes data-based FAQPage schema.

City insights

City pages, for example /in/berlin, show automatically calculated metrics such as studio count, average price, cheapest studio, top features, and share of 24/7 studios. These values are updated hourly.

Bing AI performance monitoring

Bing Webmaster Tools are used to regularly evaluate AI citations, grounding queries, most cited URLs, and impressions/clicks.

GEO/AEO Content Optimization

Studio descriptions and AI files follow GEO/AEO principles:

Fact-based sentences with consistent entities
Structured prices as Offer data
FAQ format with FAQPage schema
Clear H2/H3 hierarchy for robust parsing

AI Visibility Score

Every studio receives a score from 0 to 100. The value consists of three categories.

Profile completeness (max. 52 points)

Basic data (name, address, phone, email)
Profile image
Description with more than 100 characters
Opening hours for at least 5 days
At least 3 photos
At least one rate with a price
Website, equipment, reviews, additional services
FAQs (from Basis)
Videos (from Basis)
News/promotions (from Basis)
Awards (from Basis)
Social media profiles (Facebook, Instagram, TikTok, YouTube)

AI features (max. 35 points)

AI Profile: your studio is found more easily in 30+ AI systems (technical setup: AI description, structured data, profile page, metadata, and complete admin data set; from Plus)
AI Push: changes are submitted immediately to 30+ AI and search systems; further processing is handled by the respective provider (Premium)

Top placement (max. 13 points)

Visibility radius (2 km Basis / 5 km Plus / 10 km Premium)

Maximum score by subscription tier

The maximum achievable score depends on the subscription tier.

Tier	Max. score
Free	36
Basis	57
Plus	83
Premium	100

The score, categories, and concrete optimization recommendations can be reviewed in the studio dashboard.

Frequently Asked Questions (FAQ)

Are the files updated automatically? Yes. The sitemap generator updates the files daily. When profile changes occur, technical notifications are also sent to supported services (Premium).

Do I have to do anything technical as a studio operator? No. The infrastructure runs automatically in the background. The only relevant task is keeping the studio profile complete and up to date.

Which standards are used? llmstxt.org, Schema.org (HealthClub), OpenAPI 3.1, Croissant ML, W3C DCAT v3, W3C TDMRep, IETF AIPREF, MCP Well-Known, Google A2A, IndexNow, and Cloudflare Content Signals.

How does the AI Chat work on my website? You receive a <script> tag in the dashboard. The widget runs isolated in the Shadow DOM. The AI Chat uses live studio data from the admin area plus optional documents and streams answers via SSE.

Which data does the AI Chat use? The complete studio data set from the admin area in real time, including basic data, rates, additional services, opening hours, equipment, team, FAQs, news, videos, reviews, and review summaries. Optionally, up to 5 custom documents can be added (max. 50,000 characters).

How can I measure whether my studio appears in AI answers? Bing AI performance reports are evaluated for this, including AI citations, grounding queries, and most cited URLs.

What happens when new AI standards appear? Relevant new standards are continuously reviewed and integrated without additional effort for studios.

Conclusion

AI visibility on fragfitty.de combines technical standards, active indexing, AI News, AI Chat, AI Search, and a strong SEO ecosystem. The result: studio data is structurally available for search engines and AI systems, can be read consistently, and is continuously updated.