The reference implementation

We refuse to sell agent legibility from a site that is not agent-legible. So everything we recommend ships here, in the open. This page is the honest scorecard of our own machine layer, including the parts that are still a bet.

The machine layer, in the open

Do not trust the claims. Check them. Every artifact below is live on this domain right now.

ArtifactWhat it isInspect
Curated mapA guided index of the site for agents/llms.txt
Full exportEvery page's markdown in one fetch/llms-full.txt
Agent notesHow an agent should read this site/AGENTS.md
ManifestMachine-readable facts about us/.well-known/ai.json
Markdown twinA clean markdown version of any pagethis page as .md
Content negotiationMarkdown via an Accept headercurl -H "Accept: text/markdown" webpossible.com
Structured dataJSON-LD on every pageView source on any page

What we ship, and how much it actually matters

Green is a durable win today. Amber is cheap insurance and future-proofing, where adoption by AI crawlers is still early.

LayerWhat we shipHonest status
ReadClean HTML, full JSON-LD, markdown twin of every pageDurable win
Readllms.txt, llms-full.txt, AGENTS.md, content negotiationCheap insurance
CiteConsistent entity, sameAs links, answer-first contentDurable win
ActClear forms and actions; MCP on the roadmapIn progress
TransactNot applicable; we are not an ecommerce storeN/A
MeasureWe track our own citations across assistantsDurable win

That amber row is the part most vendors will not admit. As of now, the major training and search crawlers mostly skip llms.txt and per-page markdown, and coding agents are the ones that use them. We ship them anyway, because they are nearly free, they help the agents that do read them, and the conventions are being set right now. We would rather show you the honest picture than a green wall of checkmarks. Want to grade your own site? Use the agent readiness scorecard.

The reference implementation, answered

What is a reference implementation?
A working example that proves a method by doing it. We build WebPossible to be the most agent-legible site in its category, so every technique we teach is running here in the open. If we recommend something, you can inspect it on this site rather than take our word for it.
Do these techniques guarantee more AI citations?
No, and we will not pretend otherwise. The read and cite fundamentals (structured data, entity consistency, clean content) do move citations. The newer pieces, like llms.txt and per-page markdown, are mostly cheap insurance and future-proofing today, because most major crawlers do not consume them yet. We label which is which.
Can I copy this setup?
Yes. That is the point. The free tools give you the templates, and this page shows you the working result. Append index.md to any URL here to see the markdown layer, view the page source for the structured data, and read our llms.txt and llms-full.txt to see the curated and full exports.

Score your own site

⋅ View this page as Markdown for AI agents