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.

AVLL3 ReadyValidated agent view available

Validate your site Implementation guide

AVL Validator

Check discovery, document structure, TOON state, actions, and `llms.txt` readiness.

LIVE

AVL

Conformance check
Run a URL to see conformance, discovery, and companion checks.

No report yet

Enter a public URL and run the validator. Results, fix steps, and an AI-ready Markdown report will appear here.

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.

Human page/pricing

Agent view/pricing.agent

Agent resultLess scraping. Better citations.

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.

`@meta`, `@intent`, and discovery so agents know what a page is for.

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.

AgentViewLayer.orgOpen .agent

@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

AINode.devOpen .agent

@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.

GitHub

Reference implementation, specs, fixtures, and CMS integrations.

AI implementation brief

Give this to a coding agent and let it add AVL to a project.

This site's agent view

AgentViewLayer.org ships its own AVL routes and manifest.

npx @frontier-infra/avl validate https://example.com
curl https://agentviewlayer.org/.agent
curl https://agentviewlayer.org/agent.txt