A file-based format for recording the knowledge an AI agent needs, such as datasets, metrics, APIs, and procedures. Each bundle is made of Markdown files with YAML labels, so it can live beside code and be read without a special software library.

Use it to create, inspect, revise, validate, migrate, and maintain knowledge bundles. It supports documenting tables, datasets, views, metrics, runbooks, playbooks, APIs, and their relationships.

Agent knowledge can become scattered, hard to review, or tied to one tool. OKF gives it a consistent structure that can be versioned, checked, searched, and reused by different tools.

How saschb2b/okf-studio configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to saschb2b/okf-studio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/saschb2b/okf-studio/main/.agents/skills/okf/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/saschb2b/okf-studio

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/saschb2b/okf-studio/okf/github.svg)](https://agentmods.dev/skills/saschb2b/okf-studio/okf)

Your own site

<a href="https://agentmods.dev/skills/saschb2b/okf-studio/okf"><img src="https://agentmods.dev/badge/skills/saschb2b/okf-studio/okf/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/saschb2b/okf-studio/okf"><img src="https://agentmods.dev/badge/skills/saschb2b/okf-studio/okf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 164 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,403 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00164	$0.04403
Opus 5.5	$0.00066	$0.01761
Sonnet 5.5	$0.00033	$0.00881
Haiku 4.5	$0.00016	$0.00440

Measured 3d ago against content hash 8bacd394dc10, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

okf scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (okf-validate.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/okf/SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Open Knowledge Format (OKF)

OKF is Google's open, vendor-neutral spec (v0.2) for the context an AI agent needs, represented as a bundle. A bundle is a directory of markdown files, each a concept (a table, dataset, metric, runbook, playbook, API, join path), kept in version control next to the code it describes. Just markdown, just files, just YAML frontmatter. The format is the contract, so any producer can write a bundle and any consumer (an agent, a viewer, a search index) can read it with no SDK and no lock-in.

Use this skill two ways. Run a command on demand, or apply it implicitly whenever you shape knowledge an agent will read. The deep normative spec lives in spec.md; per-command steps in commands.md; copy-paste starting points in templates.md.

Choose the OKF method

For every OKF request, select the narrowest method that fits the user's intended outcome. In OKF Studio generic chat, call okf_capability_catalog to inspect the active versioned catalog and okf_capability_resource to load the selected method. Outside Studio, read the matching capability file directly. State the selected capability in the first progress update. Do not claim to have used a method until its resource was loaded.

User intent	Method to load
Answer a bounded bundle question or trace known links	`okf-inspect`
Select evidence, inspect the route, or diagnose a retrieval miss	`okf-retrieve`
Plan a new bundle whose destination or concept map is unresolved	`okf-create`
Add facts, citations, or relationships to existing knowledge	`okf-enrich`
Review conformance or knowledge health without changing files	`okf-audit`
Fix a reproducible validation or health defect	`okf-repair`
Reconcile bundle claims with bounded external evidence	`okf-research`
Find direct and downstream effects before a change	`okf-change-impact`
Plan a versioned schema, convention, layout, or identity change	`okf-migrate`
Turn accepted evidence and known destinations into new concepts	`okf-author`, then `writing`
Improve existing prose without changing meaning	`okf-revise`, then `writing`

Read the full file on GitHub · 128 lines

Files

What ships with it

21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

3d ago First seen · 128 lines · 164 tokens per session scan A 8bacd394dc10

Subscribe to this mod's changes

okf is a skill published in the GitHub repository saschb2b/okf-studio (47 stars, last pushed yesterday), licensed MIT. It adds 164 tokens to every session and 4,403 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-23.

Building agents Documents agents knowledge-graph markdown okf viewer

okf-loom

Load this repo skill when working with Open Knowledge Format (OKF) bundles: validate, search, discover, update, render, serve the live studio, author concepts, or use the bundled OKF docs. The repo is the distribution unit; run scripts from the checkout with scripts/okf-loom.

ojamin/okf-loom · 0 tokens

potpie-source-ingestion

Use when the user explicitly asks to ingest, refresh, or deeply understand a repository, PR, issue, ticket, runbook, incident report, document, or web link into Potpie. The harness performs todo-driven discovery, uses local/GitHub/integration tools and read-only subagents when available, builds evidence-backed…

potpie-ai/potpie · 111 tokens

potpie-resource-markdown

Use when the user asks to ingest a markdown or HTML document — an exported doc, wiki or Confluence page, web page, runbook, spec, or RFC — into Potpie so agents can search and cite it. Teaches the extraction-script flow: split on the heading tree into sections and 4k-char chunks, import with potpie resource import…

potpie-ai/potpie · 106 tokens

potpie-resource-pdf

Use when the user asks to ingest a PDF (report, contract, paper, manual, slide export) into Potpie so agents can search and cite it. Teaches the extraction-script flow: resolve the document's identity, split on the PDF's own structure into sections and 4k-char chunks, import with potpie resource import, write…

potpie-ai/potpie · 101 tokens

potpie-resource-spreadsheet

Use when the user asks to ingest a spreadsheet or CSV (cost report, inventory, tracker, export) into Potpie so agents can search and cite it. Teaches the extraction-script flow: one section per sheet, header-repeated row chunks, potpie resource import, summaries that carry the key figures, and — critically — deriving…