Google’s OKF could reduce repeated setup for AI agents
OKF, short for , is an open format for AI agents published by on June 12, 2026. The main idea is to stop explaining the same codebase or system to an AI agent every session. A project can include a `.okf/` folder with markdown files and that agents can read.
Only one field, `type`, is required. It does not need an SDK, a schema registry, or lock-in to one vendor. Unlike a single CLAUDE.md or AGENTS.md file, OKF is meant to work more like a , where related ideas link to each other through normal markdown links.
The files can live in git beside the code, so changes to project knowledge can be versioned like code. The claimed benefit is that many tools, including Claude Code, Cursor, Codex, and other agents, could read the same . OKF and RAG solve different memory problems: OKF is for structured project knowledge people maintain, while RAG is for pulling useful information from larger document sets when needed.
Key points
- OKF was published by on June 12, 2026 as an open format for AI agent knowledge.
- It uses a `.okf/` folder with markdown files and .
- Only the `type` field is required, and it avoids an SDK, schema registry, and .
- It is designed as a , not just one flat instruction file.
- Its practical value is reducing repeated context, which can lower token use and setup time.
Sources covering this story (4)
- r/RagGoogle’s OKF could reduce repeated setup for AI agents ↗
- r/RagHow do production AI systems retrieve the right knowledge from Google's Open Knowledge Format (OKF)? ↗
- r/LLMDevsI published a local agent discovery spec in January. This week Google announced the same core idea at internet scale. ↗
- r/LocalLLaMAPlurality Released: fully Free and Open Source AI agents/chatbot platform for local AI ↗