As AI answer engines became a primary discovery channel, site owners gained a new set of decisions: which AI bots to allow, how to expose content cleanly to language models, and whether to adopt emerging conventions like llms.txt. This guide clarifies what each mechanism actually does. It complements our [AI search optimization guide](/ai-search-optimization-guide/) and the citation tactics in [how to get cited by Perplexity](/perplexity-seo/).
What llms.txt Is — and What It Is Not
llms.txt is not robots.txt for AI. It does not grant or deny crawler access. It is a helper file that points models toward your best, cleanest content so they can ingest it efficiently at inference or training time. Think of it as a curated table of contents written in Markdown, often paired with an llms-full.txt that concatenates the actual content.
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## Core Guides
- [AI Search Optimization Guide](https://ottawaseo.net/ai-search-optimization-guide/): Pillar guide to AI search.
- [Generative Engine Optimization](https://ottawaseo.net/generative-engine-optimization/): How to earn AI citations.
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The AI Crawlers You Actually Need to Manage
Access is controlled through robots.txt user-agent directives, not llms.txt. Different bots serve different purposes — some train models, some power live search retrieval — and you may want different rules for each. Blocking a training bot but allowing a search bot is a common middle-ground strategy for preserving citation visibility while limiting training use.
| User-agent | Operator | Primary Purpose |
|---|---|---|
| GPTBot | OpenAI | Model training |
| OAI-SearchBot | OpenAI | ChatGPT Search results & citations |
| Google-Extended | Gemini training (separate from Googlebot) | |
| PerplexityBot | Perplexity | Indexing for answer citations |
| ClaudeBot | Anthropic | Model training |
| Applebot-Extended | Apple | Apple Intelligence training |
A Practical Access Strategy
- Decide your goal: maximum AI visibility, or maximum content control. Most publishers seeking traffic choose visibility.
- Allow retrieval/search bots (OAI-SearchBot, PerplexityBot, Googlebot) so you remain eligible for citations.
- Choose your training-bot stance (GPTBot, Google-Extended, ClaudeBot) based on how you value your content being used in training.
- Publish an llms.txt as a curated index for the engines that may adopt it — cheap insurance.
- Monitor server logs to verify which AI bots actually visit and how often.
# Allow AI search bots, block training bots (example stance)
User-agent: OAI-SearchBot
Allow: /
User-agent: PerplexityBot
Allow: /
User-agent: GPTBot
Disallow: /
User-agent: Google-Extended
Disallow: /
- Reduces unpaid use of your content for model training.
- Aligns with stricter data-governance or licensing goals.
- Blocking search bots too aggressively removes you from AI citations.
- Enforcement relies on bot cooperation; not all crawlers honor robots.txt.
- You may forfeit brand-visibility upside in AI answers.
Does llms.txt control which AI can crawl my site?
No. Crawler access is governed by robots.txt user-agent rules. llms.txt is a content-guidance file, not an access-control mechanism.
Will publishing llms.txt help me rank in AI search?
There is no confirmed ranking or citation benefit yet, because major engines have not confirmed they consume it. It is low-cost future-proofing, not a guaranteed lever.
If I block GPTBot, will I disappear from ChatGPT Search?
Not necessarily. GPTBot handles training; OAI-SearchBot handles live search retrieval. Block GPTBot but allow OAI-SearchBot to stay eligible for citations.
- llms.txt guides models to your best content; it does not control access.
- Crawler access is still managed through robots.txt user-agent rules.
- Training bots and search bots are separate — treat them differently.
- Blocking Google-Extended does not remove you from Google Search.
- Monitor logs to confirm which AI crawlers actually visit your site.