•1 min read•from Towards Data Science
How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs
Google's Open Knowledge Format (OKF) is a Markdown+YAML skeleton for sharing knowledge between humans and AI agents. This post reuses that skeleton for a very specific job — an agent-to-agent hand-off of pre-tokenized integer arrays between three Qwen2.5-Coder models (7B, 3B, 1.5B) — and shows the 28–37% TTFT reduction plus the one full-vocabulary equivalence check that keeps the whole thing safe.
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Tagged with
#OKF
#Open Knowledge Format
#LLMs
#Knowledge Exchange
#AI Agents
#Qwen2.5-Coder
#Tokenization
#Integer Arrays
#Markdown
#YAML
#Agent-to-Agent
#Model Size (7B, 3B, 1.5B)
#TTFT Reduction
#Vocabulary Equivalence
#Google
#AI
#Data Science
#Towards Data Science
#Pre-tokenized
#Hand-off