llms.txt for Webasyst Hub: community map for AI search & assistants

People increasingly skip the results page and just ask an AI: "how do I set this up", "which one fits my case", "is it compatible". The ready answer to that question already lives in your community's discussions - where your customers, and you, work through real situations. The plugin gives AI models an llms.txt - a clean map of those discussions and sections - so the AI answers with your own real replies instead of guesses, and points the person to you.

Discussions that solve a user's problem are exactly the content AI looks for to answer. Per Ahrefs (2026), visitors from AI answers convert roughly 23× better than ordinary ones, and referral traffic from ChatGPT grew 84% in eighteen months (Similarweb, 2026). The llms.txt map is what puts your site - not someone else's - inside those answers.

How AI decides whom to recommend

The same customer question - two different endings

When someone asks an AI about a complex product or service, it looks for where that question already has a solid answer. The difference is whether the AI can read your discussions - and that decides whose answer it quotes.

Without llms.txt

A customer asks an AI: "how do I choose …", "will … work for …".
The agent opens the site and sees raw HTML: menus, banners, widgets, pop-ups.
It has to guess - and takes someone else's answer, or gets yours wrong.

→ recommends a competitor or distorts your facts

With llms.txt

The same question to the same AI.
The agent reads a clean map: community sections, discussions, questions and answers.
It answers with your own real replies - the actual experience on your site.

→ recommends your community, the customer comes to you

The core - AI and problem-solving

AI sends the customer where their problem gets solved

AI models answer questions not with inventions but by quoting content that actually solves the problem: breakdowns, questions and answers, first-hand experience. Your community's discussions are exactly that kind of primary source: first-hand answers, confirmed by other members on top. That is what AI trusts and readily shows in an answer.

The plugin hands AI bots a map of those discussions, so the AI answers the customer's question from your site - and leads the person to you from there. Per Ahrefs (2026), these AI visitors are still few, but they buy roughly 23× more readily than ordinary ones: it is not about traffic volume, it is about the most ready-to-buy customers. Techniques for preparing content for AI answers (GEO) raise its visibility in them by up to +40% (a Princeton University, 2024 study).

ChatGPT
Gemini
Claude
Perplexity
DeepSeek
Alice AI · Yandex
YandexGPT

The tail two also cover the Russian market: Alice AI and YandexGPT are Yandex's leading AI assistant and model - handy if you sell to Russian-speaking customers.

Voice and chat assistants

A customer asks an assistant - the answer is assembled from your site

An assistant on a phone, in an app, a browser, a car or a speaker does not read your site itself - it passes the question to its AI model. That model, to answer, turns to AI search, which pulls data from sites and from ordinary search. Your community's data is easier and more accurate for AI search to take from a ready llms.txt map than to parse from raw HTML. The chain is simple:

Customer question Assistant's AI model AI search Site discussions + search llms.txt = a clear map of your community

Western - English-language assistants:

Google Assistant
Apple Siri
Amazon Alexa

Russia - assistants on home-grown AI (if you sell there):

Alice AI · Yandex
Marusya · VK
Salute · Sber

If the person did not name a company, the assistant picks one itself - all the more reason your discussions should be clear to it and land in the answer.

And ordinary search reinforces it

The same discussions keep working in regular search for years

An answer you gave in the community once brings people back again and again. A clear example is Stack Overflow, the largest question-and-answer forum: per Similarweb (2026), 83.94% of its traffic comes from ordinary search, and old answers stay near the top for years. A discussion archive is a compounding asset: members fill it themselves, and it brings in both search and AI traffic for free. llms.txt helps both sides at once: it gives AI a clear map, and keeps your discussion pages machine-readable for search engines too.

Why this matters right now. Classic search and AI answers are converging: Google in 2026 actually expanded its support for forum and Q&A markup, while AI search (ChatGPT and Gemini in the West, Yandex's Alice AI in Russia) increasingly answers with quotes from live discussions. A site with an accumulated body of answers wins in both channels at once.

Why our plugin specifically

Not a one-off file, but part of a system

Builds itself, nothing extra leaks. The map is built from your community's published sections and discussions and updates on changes. Drafts and hidden content never get in - only what a visitor already sees.
Your facts for AI stay in your hands. The community's name, short and full description are set in the settings and land at the very start of the map - that is exactly how the AI introduces your site.
Correct encoding on any hosting. The site engine serves the map (like robots.txt) - always clean UTF-8, no mojibake, and with no load: the file is prepared in advance, not on a visitor's request. It does not touch your theme, speed or regular SEO.
One KakTak.Net line-up. llms.txt is the community map for AI; alongside it work our Schema.org Markup (tells search engines, in machine terms, that this is a question, an answer or a discussion) and Social preview (a neat discussion card when the link is shared in chats and social networks): one style, one support, one ecosystem - instead of scattered utilities from different authors.

Stronger together

llms.txt guides AI through the community, markup and preview close the loop

These are parts of one system for preparing a site for AI search. llms.txt is the map: it shows the AI where the sections and discussions are (where to go). Schema.org Markup is the meaning of each page: whether it is a question, an answer or a discussion and how many replies it has (what to show). Social preview is a neat discussion card when the link is shared in messengers, and the person comes to you. Together they close the loop: a customer asks an AI - the AI answers with your discussions - the person comes to you - leaves a new question or answer - and finds you again through AI.

Customer asks AI llms.txt - community map JSON-LD - meaning of discussions OG preview - link is shared AI recommends - customer at your door

Schema.org MarkupMarkup for questions and discussions →

Social preview (Open Graph)A neat discussion card in chats →

Three plugins in one KakTak.Net line-up - map, meaning and preview - prepare the community for AI search together. You can start with llms.txt and add the others as you need them.

Base and premium edition

Base - one domain, premium - all domains

Base 1 domain

The site's main domain.
Full map: llms.txt and llms-full.txt - sections, discussions, questions and answers.
Scheduled and manual one-button updates.

Premium multi-domain

All community domains at once - automatically, with no per-domain setup.
Separate descriptions for each domain.
For those who run several sites from one panel.

The base edition covers the whole community with no discussion limit on the main domain and updates itself along with the content.

How it works

Quietly, in the background, without your involvement

One click builds llms.txt and llms-full.txt; after that the files update themselves on new discussions (on a schedule) or manually.
The ready file is served instantly - the build runs in advance, not on a visitor's request, and does not load the site.
llms.txt holds a short map for a quick overview, llms-full.txt a detailed one with discussion texts (length can be capped in the settings).
Everything under control: the language of the service labels (Russian, English, Ukrainian), rebuild, preview and reset of the settings - at any time.

Honest about how it works. No AI platform is obliged to read llms.txt, and on its own it does not lift your Google rankings - Google representatives say so directly. This is not a "traffic trick", it is the basic infrastructure of the AI-agent era: the effect grows as AI search spreads and is greatest paired with Schema.org markup and a rich preview when links are shared. The plugin makes your community machine-readable and honestly described - so that when an assistant reads, it reads facts and real answers, not guesses.

Community map for AI (llms.txt) for Hub app

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