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AI Context Files

5% of the total score, decided by the 3 published rules listed below.

3 rules · 5% of the score

Why this dimension exists

A cheap and optional signal. Google has stated it does not use llms.txt in Search, and crawler support is inconsistent.

Why it carries 5%

Deliberately low. Most tools in this category weight llms.txt heavily and imply it is a ranking factor; the evidence does not support that, so neither does this score.

The rules it is scored by

Each rule is a single question the scanner asks about a page. Passing one adds its share of this dimension; failing it takes that share away. Every rule links to what it looks for and what evidence passes it.

What this dimension cannot tell you

A single-URL scan reads one page. It cannot see the rest of the site, it cannot see how a model behaves over time, and it cannot see whether the page is actually cited for the queries that matter. Those are the parts of the picture a score of this kind is blind to, and they are listed in full on the methodology page rather than implied here.

Questions about AI Context Files

What does the AI Context Files dimension measure?

A cheap and optional signal. Google has stated it does not use llms.txt in Search, and crawler support is inconsistent.

Why is AI Context Files worth 5% of the score?

Deliberately low. Most tools in this category weight llms.txt heavily and imply it is a ranking factor; the evidence does not support that, so neither does this score.

What does failing AI Context Files look like?

No markdown alternate is declared on the page.

How do I improve AI Context Files?

Start with the rules worth the most, because that is where the points are. Every rule links to a page explaining what it checks and what evidence satisfies it, and a scan reports which ones a specific page currently fails.

Evidence and sources

Adding source citations produced the largest measured visibility gain for low-ranking sites, at +115%, ahead of the addition of expert quotations at +41% and statistics at +30-40%, across the strategies tested on generative engines. — Generative Engine Optimization, KDD 2024

The weighting behind this dimension follows that measurement. A failure here is reported as a rule rather than a score, so it can be checked against the page instead of taken on trust.

Primary sources