Google revealed a format for turning a physique of data right into a folder of linked markdown information. It was constructed for inner firm information, and accidentally, it solves an issue public web sites have too. Proper now, probably the most an AI agent will get out of your web site is a flat learn of your pages, separately. This format builds a graph of how your concepts join as an alternative, so I attempted it by myself web site.
Google’s Open Data Format Is A Listing Of Linked Markdown Recordsdata
On June 13, 2026, Google’s information crew revealed the Open Data Format, or OKF, a approach to characterize a physique of data as a listing of markdown information with a skinny layer of YAML frontmatter. Every idea, a desk, a metric, a runbook, an API, will get its personal markdown doc. A brief block of YAML carries the queryable fields, sort, title, description, useful resource, tags, and timestamp; the markdown physique carries the reason, and ideas hyperlink to one another with unusual markdown hyperlinks, which Google says turns the listing into “a graph of relationships.” There isn’t any runtime, no SDK, no construct step. Google describes a bundle in three phrases: “simply markdown,” “simply information,” “simply YAML frontmatter.”
The goal is inner firm data, the context Google says is “locked behind whichever floor created it,” and it’s early, v0.1, which Google calls “a place to begin, not a completed customary.” Nothing within the announcement mentions public web sites. That hole is what this piece is about.
On A Web site, A Data Graph Beats A Flat Web page-Copy
The agent-readable model of your web site, the one a mannequin or a browser really consumes, is flat. Serving every web page as markdown, the way in which Cloudflare does on the community edge, is near AMP for LLMs: a second, stripped copy of each web page for a machine to learn. It mirrors what you have already got, web page for web page, and it drops the identical factor each page-by-page copy drops, which is how the pages relate to one another.
A data graph retains that relationship layer. When your ideas hyperlink to one another, an agent not solely learns what every one is, nevertheless it additionally learns how they sit relative to one another, which is most of what understanding a web site really means. Two pages can each point out an idea and by no means inform a machine that one is the framework beneath it and the opposite is the narrower objective beside it. A graph says it outright, in hyperlinks the machine follows. OKF is an off-the-shelf approach to construct that graph: markdown, so it’s low cost, and structured, so it carries the relations.
I Tried OKF On The No Hacks Web site
I wrote an OKF bundle for the No Hacks web site, one markdown file every for the model, the host, Machine-First Structure, the agentic internet, Agent Expertise Optimization, Reply Engine Optimization, llms.txt, and WebMCP. Every follows Google’s conventions, the YAML fields on high and a plain markdown physique beneath. The work was largely deciding which ideas mattered and the way they join, not writing the information.
One file, the idea for Machine-First Structure, appears like this:
---
sort: framework
title: Machine-First Structure
description: A framework for constructing web sites whose full which means is out there to a machine studying them, with the human expertise layered on high moderately than the opposite method round.
useful resource: https://machinefirstarchitecture.com
tags: [Framework, Machine-First Architecture, Agentic Web]
timestamp: 2026-06-13
--- Machine-First Structure is [Sani](./sani.md)'s framework for the [agentic web](./agentic-web.md). The core concept: construct the content material so a machine studying it will get the whole which means, the info, the construction, the relationships, and the human studying will get that very same which means with the design on high. For this reason codecs that strip a web site to plain textual content, like markdown for brokers and [llms.txt](./llms-txt.md), matter. Its functionality aspect is [WebMCP](./webmcp.md), and its measurement aspect is [Agent Experience Optimization](./agent-experience-optimization.md).
These bracketed hyperlinks on the backside are the graph. An agent following them learns that WebMCP sits underneath Machine-First Structure, and llms.txt is identical form of wager, which a flat copy of my pages by no means says out loud. Throughout the eight information, that’s the entire construction: ideas, and the relationships between them.
A bundle like it is a second copy of what the web site already says, and a second copy is a second factor to maintain in sync. The second the web site adjustments, the bundle is incorrect till you replace it too. That tax will not be distinctive to OKF: it’s what each parallel machine-readable layer prices, an llms.txt file, a markdown mirror of your pages, a bundle like this one. The model an agent reads is just as correct as your self-discipline in conserving it present.
Google didn’t construct OKF for this. Its goal is inner firm data, and nothing in its plan factors at public web sites, so internet hosting a bundle for a visiting agent is off-label, and it could keep that method. The reader I made it for, an agent that fetches the bundle and follows the graph, may by no means present up. The explanation to do it has to face with out that payoff, and it does: writing the bundle pressured me to state plainly what No Hacks is aware of and the way its concepts join, and that surfaced gaps I’d not have discovered writing one other web page. It’s the similar self-discipline as Machine-First Structure, put your which means in a type a machine can learn, and you discover the place you had been imprecise.
The place A Web site Data Graph May Lead
None of what follows is a prediction. It’s a route, and it depends upon brokers really studying web site data graphs, which at this time, none do. The form remains to be value seeing.
The id file might develop right into a data graph. Immediately, llms.txt is a single line asserting who you might be. A printed bundle is the total model of that concept, a map of all the pieces your web site is aware of and the way the elements join, so the skinny id layer and the structured data layer change into one factor.
Brokers might question that map as an alternative of scraping your pages. An agent that pulls your bundle and follows its hyperlinks will get a cleaner, relationship-aware learn than one parsing your HTML one web page at a time, and also you get extra say in how your personal ideas are represented when an AI describes you.
The map might even change into the canonical layer. The model a machine reads stops being a duplicate of your web site and turns into the supply, with the human pages as one rendering of it. That’s the totally machine-first web site the agentic internet has been pointing at, reached via a aspect door Google opened for inner information.
Markdown Is Not New
John Gruber created Markdown in 2004, with Aaron Swartz as his beta-tester, and the entire design objective was readability: textual content you possibly can learn as-is, with out rendering, that also converts cleanly to HTML. Twenty years later, it runs GitHub, Reddit, a lot of the documentation you learn, and the chat containers of the AI instruments themselves. It gained by being legible with out being rendered, which is the precise property that makes it straightforward for a machine to learn.
I’ve written most of what I write in it for 15 years, since iA Author grew to become my principal writing app in September 2011, so per week when the agent-readable internet converges on markdown is acquainted floor to me, not a brand new trick. The data behind No Hacks (No Hacks OS mission) has run the identical method for months: markdown information with structured frontmatter, linked to one another, the form a machine can learn and traverse.
Machine-facing codecs preserve touchdown on that very same floor, llms.txt, Cloudflare’s markdown, and now OKF. Google itself will not be of 1 thoughts about it. Its Search aspect referred to as llms.txt “purely speculative” for rating, its Chrome aspect added an llms.txt test to Lighthouse’s agent-readiness audit, and its information crew has now revealed OKF.
If you wish to see the place your web site stands, it takes thirty seconds. Open your most vital web page and paste it right into a plain-text editor, the place the hyperlinks collapse into plain phrases. Have a look at what’s left and discover something that states how its concepts relate to the remainder of your web site, not that one web page hyperlinks to a different, however the relationship itself. There’s often nothing, and that absence is what a data graph fills, whether or not or not you ever contact OKF.
OKF is that this week’s information, and the substrate underneath it, plain textual content a machine can learn, has been right here since 2004. What Google added was a typical and a reputation.
Extra Sources:
This submit was initially revealed on No Hacks.
Featured Picture: Roman Samborskyi/Shutterstock
