Google announced the Open Knowledge Format (OKF), a new open specification for organizing and exchanging the knowledge that AI systems need in order to perform useful work.
The announcement explains the reason for developing this new specification:
“As foundation models continue to improve, the lack of relevant context often limits what they can do, especially as they are used to build agentic systems. While these models can help you write code, summarize documents, or analyze a dataset, they still need the right information to produce accurate and actionable results. “
AI Agents Need Context
AI systems often need knowledge that exists outside the model, including how data is structured, how systems work, how metrics are defined, and how internal processes operate.
That knowledge is usually scattered across catalogs, wikis, documentation, repositories, shared drives, and other internal systems, forcing AI agents to assemble context before they can complete a task.
Google says OKF is meant to solve that problem by turning scattered knowledge sources into a common format that can move between humans, AI agents, tools, and organizations.
What Open Knowledge Format Is
OKF is a format for representing organizational knowledge in a way that can be shared between different AI agents, tools, and organizations.
The format organizes concepts such as datasets, metrics, APIs, tables, and runbooks into documents that can be read by both humans and AI systems.
Google designed OKF to be simple and independent of any specific platform, allowing the same knowledge to be shared between different AI agents, tools, and organizations.
The announcement explains:
“To make the format concrete, we’re publishing reference implementations at both the producer and consumer ends:
- An enrichment agent that walks a BigQuery dataset, drafts an OKF concept document for every table and view, then runs a second LLM pass that crawls authoritative documentation and enriches each concept with citations, schemas, and join paths.
- A static HTML visualizer that turns any OKF bundle into an interactive graph view in a single self-contained file; no backend, no install on the viewing side, no data leaves the page.
- Three ready-to-browse sample bundles: GA4 e-commerce, Stack Overflow, and Bitcoin public datasets, produced by the reference agent and committed to the repo as living examples of conformant OKF.
These are proofs of concept, deliberately. The agent demonstrates one way to produce OKF; nothing about the format requires a specific agent framework or LLM. The visualizer demonstrates one way to consume it; nothing about the format requires HTML or a graph view. We expect (and want!) the ecosystem of producers and consumers to grow far beyond what we’ve shipped.”
Who OKF Is For
OKF is designed around a producer-and-consumer model. Some users create, edit, and maintain the knowledge. Others consume it through AI agents, LLMs, software systems, or internal tools.
AI Agents…
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