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okf-opslisted

Assess, validate, and adopt the Open Knowledge Format (OKF) across markdown+frontmatter knowledge bases. Use to scan a doc repo for OKF-readiness (how frontmatter-consistent it already is), validate a bundle for conformance, find good OKF-adoption candidates among many repos, or migrate a frontmatter-heavy repo onto OKF. Triggers on: OKF, open knowledge format, knowledge bundle, knowledge base format, assess docs, doc repo readiness, frontmatter conformance, validate frontmatter, type frontmatter, markdown knowledge base, adopt OKF, is this repo OKF-ready, index.md log.md.
0xDarkMatter/claude-mods · ★ 22 · AI & Automation · score 74
Install: claude install-skill 0xDarkMatter/claude-mods
# OKF Ops The **Open Knowledge Format (OKF)** is a minimal, open convention for representing *knowledge* as a directory tree of markdown files with YAML frontmatter — the metadata and curated context that surrounds data and systems. This skill helps you **assess** whether a repo is a good fit, **validate** a bundle for conformance, and **adopt** OKF where it earns its keep. Full format rules: [references/okf-spec.md](references/okf-spec.md). Copy-ready concept doc: [assets/concept-template.md](assets/concept-template.md). ## Honest scope (read this before adopting) OKF is a **v0.1 draft** (Google-published, platform-agnostic). It's deliberately minimal: one required frontmatter field (`type`), reserved `index.md`/`log.md`, and a *permissive-consumption* contract. Two consequences worth knowing up front: - **Adoption cost is shaped by the repo, not the size.** A repo that already uses frontmatter consistently is often one mechanical `type`-derivation pass from conformant. A repo of bare prose markdown needs frontmatter authored on every file — often not worth it, and arguably the wrong files to make "concepts." - **Conformance is a weak guarantee.** "OKF-conformant" means the structural floor is met, not that the content is good. Use the assessment to decide adoption per-repo; don't make it a blanket mandate. The tools here are useful **regardless of OKF's trajectory** — `assess-okf.py` is a general "how frontmatter-consistent is this doc tree?" scanner. ## Wo