Definition
Agent readiness
Agent readiness is how well a website can be used by an automated agent rather than a person: stable URLs, server-rendered content, structured data, explicit crawler rules and machine-readable endpoints.
The term comes from the observation that an agent and a human need different things from the same site. A person tolerates a JavaScript-rendered page, an interstitial and a navigation menu. An agent needs the answer in the response body, a URL that will still resolve next month, and a declared place to look for capabilities. An independent community spec at specification.website defines it around stable URLs, structured data, clean semantics, robots controls and machine-readable endpoints.
Agent readiness overlaps with AI readiness but is not the same scope. AI readiness asks whether an answer engine can crawl, parse, understand and cite the site. Agent readiness adds the question of whether software can act: find an API catalog, read an MCP server card, negotiate a markdown representation, complete a task without a browser.
It is measurable today, which is the useful part. Every element listed above is a request you can make and an answer you can score, which is how our readiness audit treats it: 36 checks in five weighted categories, with the checks that gate everything else (crawler access, rendering without JavaScript) capping the score when they fail.
Frequently asked questions
Is agent readiness the same as AEO or GEO?
No. AEO and GEO are about being cited in generated answers. Agent readiness is about whether software can read and act on the site at all, which is a precondition for being cited but a wider question.
What is the fastest way to improve agent readiness?
Serve your primary copy in the HTML response and confirm no edge rule blocks AI user agents. Those two decide whether anything else you do is visible, which is why both are gating checks in our model.