This week, we break down two emerging specs shaping how content is served to large language models. llms.txt introduces a simple way to manage AI access, while llms-full.txt pushes the idea further with a structured, developer-friendly format designed to bundle context, metadata, and usage intent into every page.
In response, some developers have proposed a new standard: LLMs.txt. The standard suggests creating machine-readable entry points for models, akin to what robots.txt is for crawlers, but optimized for inference rather than indexing.
It sounds promising on paper, but in practice, it’s inconsistently implemented, unsupported by major AI providers, and arguably premature. Here we’ll take a closer look at the LLMs.txt standard, the files it proposes, and whether it’s worth implementing.
📖 Read more here.
LLMs-Full.txt is an unofficial format for consolidating important web content, like API docs, onboarding guides, or support pages, into a single markdown file. It’s not part of the llms.txt standard.
📖 Read more here.
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Until next time,
Thenuka
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