Evaluate whether to implement an llms.txt file for a site and set expectations about its actual effect on AI crawler/agent behavior

Steps

1. Read the current llms.txt specification at llmstxt.org before implementing, since it is a community-maintained convention (a Markdown file at /llms.txt summarizing site content/links for LLMs), not an IETF or W3C standard
2. Check whether any AI platforms your audience actually uses are known to request or use llms.txt in practice, since major crawlers (OpenAI, Google, Anthropic) have not been shown to request it in meaningful volume as of 2026
3. If proceeding, keep the file to a concise Markdown summary with links to canonical documentation/content pages, generated or updated alongside your normal publishing pipeline so it doesn't go stale
4. Do not treat llms.txt as a crawl-control or opt-out mechanism — it has no directive semantics like robots.txt and does not block or permit crawling on its own
5. If on a platform (e.g. certain e-commerce platforms) that auto-generates an llms.txt for you, review the auto-generated content rather than assuming it's accurate or complete
6. Frame this to stakeholders as a low-cost, unproven-ROI experiment rather than a required or high-impact SEO/AEO tactic, given adoption and consumption remain limited and unstandardized