Agent-readiness guides
Short, focused explanations of the surfaces that decide whether an AI agent can discover, read, and act on a website or an API. Each guide covers one topic.
Discovery and content - What an agent-readiness audit is - llms.txt explained - Serving markdown to agents - Sitemaps, robots.txt and agent access - Response headers that help agents - Prerendering and why agents see empty pages
Capability and trust - MCP server cards explained - What agents.json is - The /.well-known directory for agents - How agents authenticate - JSON-LD and structured data for agents
Commerce and strategy - x402 and agent payments - SEO and agent-readiness are not the same - Why agent-readiness should be measured, not asserted - Common agent-readiness gaps on marketing sites
Frequently asked
### What is an agent-readiness audit? An agent-readiness audit measures how well an AI agent can discover, read, and act on a website or an API, scored against current standards by an independent scanner rather than a self-assessment.
### Do I need llms.txt on my site? If you want models and agents to read your real content rather than guess from a cached snippet, llms.txt gives them a curated map of what matters. It does not replace robots.txt or a sitemap, it complements them.
### How do I get my site cited by AI assistants? A model cites content it can read cleanly and corroborate. That means machine-readable surfaces such as llms.txt and structured data, a markdown form that does not exhaust the token budget, and being indexed where the assistant searches.
### What is an MCP server card? An MCP server card is a JSON file, usually at /.well-known/mcp/server-card.json, that lets an agent discover a site's Model Context Protocol server and the tools it exposes, so the agent can call them without a human wiring up the connection.
### Is agent-readiness the same as SEO? No. SEO makes a site rank for a person to click. Agent-readiness makes a site legible and usable by an agent that reads and acts. A site can rank well and still be opaque to agents.
### How is agent-readiness measured? By an independent scanner that reads the live site and reports a score with a category breakdown. The categories that get fixed read higher on the next scan, so the claim is the number rather than an assertion.
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