`@meta`, `@intent`, and discovery so agents know what a page is for.
Agent View Layer
A producer-owned web view for AI agents. Publish clean `text/agent-view` companions so agents can understand pages without scraping pixels.
Put in a URL and see whether agents can discover, read, and cite the site from its own structured companion view.
AVL Validator
Check discovery, document structure, TOON state, actions, and `llms.txt` readiness.
Run a URL to see conformance, discovery, and companion checks.
discovery.page_agent
document.intent
companion.llms_txt
What is AVL?
AVL gives every human page a parallel agent view. The site owner publishes the facts, intent, actions, context, and navigation directly, so agents do not have to guess from layout.
Conformance that starts useful and grows up.
AVL adoption should not require a rewrite. Start with intent and discovery, then add structured state, actions, context, and navigation.
Add `@state` so agents can read page data without DOM scraping.
Add `@actions` so agents can understand the affordances available.
Add `@context` and `@nav` for meaning, traversal, and citations.
Real `.agent` outputs.
AVL is intentionally readable. These are the kinds of companion views an agent can fetch before deciding what to do next.
@intent
purpose: Public standards home and validator
audience: developer, maintainer, ai-agent
capability: validate, learn, implement, cite
@actions
- id: validate_url
method: POST
href: /api/validate@meta route: / @state product: AINode category: local AI infrastructure @nav self: /.agent parents: [/]
Built for adoption.
The public site is the front door. The GitHub repo remains the source of truth for the package, spec, CMS adapters, fixtures, and validator.
npx @frontier-infra/avl validate https://example.com curl https://agentviewlayer.org/.agent curl https://agentviewlayer.org/agent.txt