What this llms.txt generator creates
The generator creates a concise public file that gives AI assistants a curated map of important URLs. It is not a replacement for sitemap.xml; it is a human-readable discovery guide for AI systems.
- Creates a structured llms.txt draft with site name, description, audience, and important URLs.
- Supports manual URL lists, a homepage URL, or selected URLs from a sitemap.
- Keeps the file short enough to be useful instead of dumping every page.
- Provides deployment steps for publishing the file at the site root.
When to use llms.txt
Use it when your site has product, pricing, docs, blog, or resource pages that should be easy for AI assistants to cite and understand. It is especially useful for SaaS and expert content sites.
- Before launching a new AI-search or GEO visibility program.
- After restructuring product or documentation URLs.
- When you want AI assistants to discover canonical pages quickly.
- When your sitemap is too broad to communicate editorial priorities.
How to interpret the output
A good llms.txt file should be short, canonical, and intentional. It should highlight the pages that explain what the business does, how users can evaluate it, and where trustworthy resources live.
- Keep only public URLs that should be discovered and summarized.
- Prefer canonical product, pricing, docs, tools, and resource pages.
- Use the description to clarify audience and value, not marketing fluff.
- Review the file after major product or content changes.
Common llms.txt mistakes
The biggest mistake is treating llms.txt like another sitemap. AI assistants need a curated guide, not a dump of every paginated, filtered, or low-value URL on the domain.
- Do not include private, checkout, staging, or parameter URLs.
- Do not duplicate sitemap.xml inside llms.txt.
- Do not list pages that are noindex, blocked, or canonicalized elsewhere.
- Do not publish the file once and forget it after site changes.
Next step after generating llms.txt
Publish the file at /llms.txt, confirm it is crawlable, and make sure the highlighted URLs are technically clean. AI visibility still depends on strong canonical, indexability, content, and authority signals.
- Validate that important URLs return 200 and self-canonical signals.
- Use sitemap extraction to choose high-value URL groups.
- Use robots and indexability tools to confirm AI-accessible crawl paths.
- Use Spider Analysis when highlighted URLs need technical cleanup.
- Document the URL group, owner, expected impact, validation step, and next publishing decision so the result becomes a fix ticket instead of another exported spreadsheet.
