Make your purpose machine-readable

An agent that cannot parse what your product does cannot use it or cite it. Expose your purpose through structured data, semantic HTML, an llms.txt index, and hosted context files.

Why

Stripping HTML chrome to markdown cuts agent tokens 80–90% and improves retrieval (Cloudflare/Fern analysis). The canonical AX framework (agentexperience.ax — Contextual Alignment) requires that services actively provide context because agents must not be assumed to have sufficient internal context or a correctly trained model. Biilmann identifies this as the Context pillar: "does the LLM know about your product?"

Do

Ship /llms.txt, JSON-LD structured data, and clear <meta> descriptions. Also provide hosted context files agents can use directly: AGENTS.md (coding agent rules), Agent Skills files, and Arazzo workflow specs for complex multi-step interactions. See agentexperience.ax for the full context file ecosystem.

Don't

Rely on JS-rendered pages with no structured data, or assume the model was trained on current documentation about your product.

Artifact

/llms.txt:

# Acme
> One-line description of what Acme does.
## Docs
- [Quickstart](https://acme.com/docs/quickstart.md): get running in 5 minutes
- [API reference](https://acme.com/docs/api.md): endpoints and schemas

Pair with JSON-LD on key pages:

<script type="application/ld+json">
{"@context":"https://schema.org","@type":"SoftwareApplication","name":"Acme",
 "description":"Acme helps teams do X.","url":"https://acme.com",
 "offers":{"@type":"Offer","price":"29","priceCurrency":"USD"}}
</script>