Rafael LopesPeople increasingly don't visit your site — an AI agent visits it for them, reads what it can, and reports back. Whether that agent finds you, understands you, and can act for you comes down to a handful of concrete web standards. This course covers all of them, foundational to emerging, each with copy-paste implementation and a way to measure it.
Measure any page against every one of these with the Core Agent Vitals analyzer — its Agent Discoverability panel links each check straight back to the matching lesson below.
Module 1 — Foundations: can an agent read it?
The standards agents already respect. Get these wrong and you're invisible.
- AI-Aware robots.txt — let the right AI crawlers in; a stale
Disallowerases you from agent answers. - Sitemaps for Agent Discovery — the table of contents that gets your deep pages found.
- JSON-LD Structured Data — tell agents what a page is, in typed facts, not prose.
Module 2 — LLM-native: is it legible and callable?
Purpose-built signals for language models and tool use.
- llms.txt & llms-full.txt — a curated, machine-readable map an agent reads in one cheap fetch.
- API Docs for Agent Tool Use — an OpenAPI spec turns your API from guessed to callable.
Module 3 — Emerging: can an agent operate it?
Where the agentic web is heading — early, optional, worth understanding now.
- agents.json Capability Declaration — declare what your site can do, not just what it says.
- WebMCP for Websites — let agents call your actions directly instead of scraping.
Start at lesson 1, or jump to whatever your analyzer results flag as missing.