llms.txt as an LLM standardized parsing tool
llms.txt is a standard document format supported by industry leaders such as Cloudflare, Anthropic, and others, created specifically to address the pain points of processing website information in the Large Language Model (LLM). Traditional HTML documents contain complex tag structures, advertisement scripts, and dynamic content, which creates significant barriers to information extraction by AI. llms.txt provides concise, structured data through Markdown formatting, and is designed to be similar in concept to what robots.txt is to search engine crawlers. The core value of this solution is twofold: first, it reduces the waste of LLM's computational resources by eliminating the need to parse irrelevant content; and second, it ensures that critical information, such as API documentation and developer guides, can be accurately identified and utilized.
Practical examples show that this standard, proposed by Answer.AI co-founder Jeremy Howard, has been adopted by technology companies such as Mintlify, significantly improving the efficiency of LLM's retrieval of document information by about 37% by automatically generating the /llms.txt and /llms-full.txt files.This standardized approach is forming a new industry specification and is expected to be adopted by the end of 2024 for 801 TP3T of technical documents.
This answer comes from the articlellms.txt: Standardized Site Information Documentation for Large Language ModelsThe
