Foundation models keep getting stronger, yet they still stall on the same thing: context. A model can write code or analyze a dataset, but only with the right internal knowledge. That knowledge includes table schemas, metric definitions, runbooks, join paths and it lives scattered across catalogs, wikis, and a few senior engineers’ heads.

Google Cloud introduced the Open Knowledge Format (OKF), an open specification that formalizes the LLM-wiki pattern into a portable, interoperable format. It is a vendor-neutral, agent- and human-friendly standard for the context modern AI systems need.

Open Knowledge Format (OKF)

OKF is a format, not a service or a platform. OKF v0.1 represents knowledge as a directory of markdown files with YAML frontmatter. A small set of agreed-upon conventions lets wikis written by one producer be consumed by a different agent without translation.

That is the whole idea. There is no compression scheme, no new runtime, and no required SDK. A bundle of OKF documents is just markdown, just files, and just YAML frontmatter. It renders on GitHub, ships as a tarball, and mounts on any filesystem.

If you have used Obsidian, Notion, or Hugo, the shape will feel familiar. OKF only formalizes the conventions needed to make those patterns interoperable.