Proposal for inline LLM instructions in HTML based on llms.txt

The proposal introduces an innovative method for embedding instructions for AI agents directly within HTML responses using a <script> tag with the type "text/llms.txt". This approach aims to simplify how AI agents access protected web pages by providing them with in-line guidance, thereby eliminating the need for external documentation or pre-configured knowledge. Vercel, which protects preview deployments by default, has implemented this method on its 401 error pages to guide automated agents on how to bypass authentication using specific functions from the Vercel MCP server. The <script> tags with an unknown type are ignored by browsers but can be read by AI, making them an ideal medium for delivering instructions without affecting the user experience. This method aligns with the emerging llms.txt standard, which is designed for publishing AI-targeted content on the web, and offers a straightforward way for AI agents to discover and utilize available mechanisms for accessing protected content. The flexibility of this approach means it can be adopted immediately without requiring formal standardization or coordination with major AI providers.