There is no formula that makes an AI system cite a document. However, a page whose evidence is difficult for people to locate may also present unclear context to automated systems. Citation readiness is less about hidden optimization than about making questions, answers, and evidence explicit.
Difficult documents weaken the link between title and content
When several topics sit under an abstract heading, definitions exist only inside images, or units and sources are separated from a table, the scope of an answer becomes unclear. Without dates and revision status, readers cannot judge whether the evidence is current.
Easier documents separate answers by question
Let each section answer one question. Give a direct response first, then explain conditions and exceptions. Add a title, unit, period, and source to each table, and describe its relationship in prose. Use a distinct page title and description.
Keep claims close to original evidence
Connect figures and comparisons to the source document, research scope, and update date. If a page cites another summary, make the primary source traceable. Feat AI Citation presents a direction for AI-readable and citation-ready structure, but it does not guarantee a citation rate.
Questions before publishing
- What is the main question this page answers?
- Does the opening state the answer’s scope and conditions?
- Can readers open the source behind every table and figure?
- Are authoring, revision, and ownership details visible?
- Did editing create a stronger claim than the source?
Good structure is not only for AI. It also helps readers verify evidence and teams maintain the document.