Open Knowledge Format
What this page covers
This page contains verified factual information extracted from public source pages. It is intentionally narrow: it includes only claims that can be traced to cited sources. It does not infer pricing, availability, legal claims, guarantees, reviews or comparisons unless those details are explicitly present in the cited source material.
How to evaluate this page
A fair evaluation should check whether the page is crawlable, readable without JavaScript, source-linked, concise, internally consistent and clearly subordinate to the original website. The goal is not to create a second conversion page. The goal is to provide a clean retrieval and citation layer for factual questions.
Definition
What is it: The Open Knowledge Format is a vendor-neutral standard for representing the metadata, context, and curated knowledge that modern AI systems require. It is designed to be read by people and parsed by agents without the need for a translation layer.
What is it used for: It is used to formalize the LLM-wiki pattern, creating a library of markdown files that agents can read and cross-reference. Each file represents a concept such as a dataset, table, metric, runbook, or API.
What it is not: It is a format rather than a platform, and it does not include an SDK, proprietary runtime, or compression scheme.
Coverage
- Attributes: 6
- Synonyms: 1
- Related entities: 3
- Sources: 1
Identity
- Entity ID
- https://llms.getfaind.com/en/open-knowledge-format/facts/#entity
- Entity type
- DefinedTerm
- Canonical name
- Open Knowledge Format
- Language
- en
- Topic
- Open Knowledge Format
Attributes
- Key Facts
- Google Cloud published the Open Knowledge Format on June 12, 2026. [1]
- Key Facts
- The Open Knowledge Format represents metadata and curated knowledge that AI systems consume as a machine-readable layer. [1]
- Key Facts
- An OKF bundle is a directory of markdown files where each file represents a single concept such as a dataset or runbook. [1]
- Key Facts
- Each OKF file contains structured metadata in YAML frontmatter followed by a markdown body with links between documents. [1]
- Key Facts
- FAIND builds a machine-readable Knowledge Graph that functions as a separate, agent-readable layer for brands. [1]
- Limitation
- The OKF v0.1 specification is minimally opinionated and requires only a title field. [1]
Synonyms & Alternate Names
- OKF
Related Entities
- Published by:
- Formalizes:
- Implementation example:
Provenance
- Official source: https://getfaind.com/insights/googles-open-knowledge-format-and-the-agent-readable-web
- Last modified:
Sources
- https://getfaind.com/insights/googles-open-knowledge-format-and-the-agent-readable-web (Open Knowledge Format)
Machine metadata
- page_type: facts
- canonical_url: https://llms.getfaind.com/en/open-knowledge-format/facts/
- entity_id: https://llms.getfaind.com/en/open-knowledge-format/facts/#entity
- entity_type: DefinedTerm
- entity_name: Open Knowledge Format
- topic_slug: open-knowledge-format
- topic_id: topic-en-open-knowledge-format
- hub_url: https://llms.getfaind.com/en/open-knowledge-format/
- source_url: https://getfaind.com/insights/googles-open-knowledge-format-and-the-agent-readable-web
- brand: getfaind.com
- date_modified:
- language: en
- attributes_count: 6
- related_count: 3
- sources_count: 1
- schema_version: 3