Does llms.txt increase AI citations? | Trakkr Research

Q: Which numbers from The llms.txt Effect matter most here?

Median citations with llms.txt: 3. Median citations for domains with llms.txt. Median citations without llms.txt: 3. Median citations for domains without llms.txt.

Q: What should a team do next?

Treat llms.txt as an optional housekeeping file, not a primary citation-growth lever. Prioritize answer quality, source coverage, and page structure before spending disproportionate effort on llms.txt. If you do publish llms.txt, measure discovery and crawl behavior directly instead of assuming it improved citation performance.

This snapshot does not establish a causal increase. The top-5,000 test returns p=0.85, while the full 37,894-domain sample returns p<0.001 with reported r=-0.065.

Methodology: Built from HTTP scans of 37,894 AI-cited domains, linked to 337,362 citations and 882 citation snapshots in the Trakkr corpus.

Direct Answer

This snapshot does not establish a causal increase. The top-5,000 test returns p=0.85, while the full 37,894-domain sample returns p<0.001 with reported r=-0.065.

What this means

This answer matters because it turns a study finding into an operating rule teams can use when they decide what to publish, refresh, or measure next.

Evidence table

Metric	Value	Why it matters
Median citations with llms.txt	3	Median citations for domains with llms.txt.
Median citations without llms.txt	3	Median citations for domains without llms.txt.
Average citations with llms.txt	6.8	Mean citations for domains with llms.txt.
Average citations without llms.txt	6.7	Mean citations for domains without llms.txt.
Top-5,000 Mann-Whitney p-value	0.85	Subset of the top 5,000 cited domains; not the full-sample test.
Full-sample Mann-Whitney p-value	<0.001	Full 37,894-domain sample. The public JSON rounds this value to zero.
Full-sample reported effect size r	-0.065	Small reported magnitude; not an estimate of causal citation lift.

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