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Markdown Doesn't Matter in AI Search (Yet)

Based on 1,665,674 citations (last 7 days) from ChatGPT, Claude, Perplexity, and Google AI Overviews, markdown files account for just 0.05% of all AI search citations. Despite the hype, AI search engines almost never cite .md files. Markdown is a format built for AI agents and developer tooling, not for search visibility.

OpenAI Claude Citation Share by Content Format

Based on 1,665,674 citations (last 7 days) across ChatGPT, Claude, Perplexity, and Google AI Overviews. These results aren't inconclusive or misleading: markdown simply does not influence citations in AI search. There are plenty of reasons to use .md files, but optimizing for AI search shouldn't be the strategy.

HTML

99.94%

Markdown (.md)

0.050%

Images

0.015%

Markdown is not for AI search. It's for AI agents

At just 0.05% of citations, .md files are virtually absent from AI search results. ChatGPT Search and AI Overviews cite HTML web pages, news articles, forums, and documentation sites, not raw markdown files. The confusion between AI search and AI agents has led to misplaced optimization efforts.

Where markdown does matter is in the rapidly growing world of AI coding agents. We're seeing a huge uptick in documentation and site information being crawled by Claude's bot (powering Claude Code) and OpenAI's bot (powering Codex). These agents don't search the web the way ChatGPT Search does. They fetch specific docs, READMEs, and API references to complete coding tasks. Markdown is simpler, cleaner, costs less parsing time, and keeps the context window clean. This shift is accelerating with new agent-native search engines like Exa, already integrated into tools like OpenCode, that let agents search the web and retrieve URLs on their own. As more AI agents adopt these purpose-built search layers, the gap between consumer-facing AI search and developer-facing AI agent retrieval will only widen.

Request PathRequestsCrawlers
/docs/****/************.md3,241
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/****/*********.md2,870
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/******/************.md1,934
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/****/**********.md1,512
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/******/****************.md1,207
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/********/*************.md986
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/****/****************.md743
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/******/********.md651
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/********/**********.md489
Claudeanthropic-claudebotOpenAIopenai-searchbot
/docs/****/*******************.md372
Claudeanthropic-claudebot
/docs/********/****************.md318
OpenAIopenai-searchbot
/docs/*****/**********.md245
OpenAIopenai-searchbot
/docs/***********/**********.md189
OpenAIopenai-searchbot
.........

How we collect this data

We collect millions of prompt responses, citations, and click data from the actual user interfaces of major AI platforms — over 1 billion data points and growing. This gives us one of the largest and most authentic datasets on how AI search engines cite sources and recommend brands.

Real UI monitoring

We collect data from the interfaces of ChatGPT, Gemini, Perplexity, Claude, AI Overviews, and more — the same results hundreds of millions of users see daily.

1B+ data points

Our dataset spans over 1 billion analyzed citations, prompts, and responses — giving us one of the largest AI search datasets available.

Aggregated & public

We publish these reports freely so the GEO and AI search community can learn from the data. All reports are based on aggregated, non-identifiable trends.

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