Awesome-OKF

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Guvenlik Denetimi
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Bu listing icin henuz AI raporu yok.

SUMMARY

OKF (Open Knowledge Format) — curated catalog of tools, plugins, skills, proposals, and docs for agent-friendly knowledge. YAML-driven, agent-searchable, MCP-ready.

README.md

Awesome OKF

Awesome OKF

The curated catalog of Open Knowledge Format resources.

YAML-driven. Agent-searchable. Community-curated.

Awesome License Catalog OKF Anything

English | 中文 | 日本語 | 한국어


Catalog  ·  Connect an Agent  ·  CLI  ·  Contributing



What is OKF

Open Knowledge Format (OKF) is an open specification by Google Cloud — define knowledge as a directory of Markdown files with YAML frontmatter and a small set of conventions. No runtime, no SDK.

What's Different Here

Awesome OKF keeps the entire OKF ecosystem in one validated YAML catalog, then turns it into a browsable list, a searchable CLI, and an MCP meta-server that AI agents can query directly:

                      catalog.yaml
                           │
          ┌────────────────┼────────────────┐
          ▼                ▼                 ▼
      README.md         CLI tools        MCP server
   (human-browsable)  (searchable)   (agent-searchable)

Edit one record. Regenerate the docs. Re-query from anywhere.


🌐 OKF Anything

Anything readable → OKF. Every format above — and any you invent — collapses into one intermediate shape, then bundles into OKF:

        ┌────────── EXTRACT ──────────┐   ┌── NORMALIZE ──┐   ┌──── BUNDLE ────┐
        │  Markdown · Typora · PDF    │   │  title         │   │  # title       │
        │  Obsidian · Notion · Feishu │ → │  url           │ → │  description   │
        │  GitHub · JSON · YAML       │   │  description   │   │  resource      │
        │  CSV · key-value · OCR      │   │  body / tags   │   │  myokf-ready   │
        └─────────────────────────────┘   └────────────────┘   └────────────────┘
  1. Extract — pull readable text out of any source. Platform exports and local engines (pymupdf, PaddleOCR) do the lifting; nothing runs through our model.
  2. Normalize — every format reduces to title / url / description (+ optional body, tags).
  3. Bundle — render the intermediate shape into a myokf-validatable OKF directory.

--format anything is the programmatic form: feed it arbitrary text and it walks the parser chain (list → JSON → key-value → URLs → line-per-row) until one sticks:

python scripts/convert-to-okf.py whatever.txt --format anything -o kb/

The MCP tool convert_to_okf speaks the same idea — an agent hands it arbitrary text, it hands back OKF.


See It in Action

User (or Agent):
  "Find an OKF plugin for Obsidian vault conversion."

Agent calls:
  search_catalog({
    "query": "Obsidian",
    "kind": "plugin",
    "limit": 3
  })

Awesome-OKF responds:
  ┌──────────────────────────────────────────────────────────────┐
  │ obsidian-to-okf                                plugin        │
  │ Convert Obsidian vaults to OKF — wikilinks become OKF links. │
  │ Platform: python  ·  Tags: obsidian, wikilink, markdown      │
  └──────────────────────────────────────────────────────────────┘

The catalog speaks OKF.


Quick Start

Connect to Your Agent

Add Awesome OKF to any MCP client so your agent can discover OKF resources:

pipx install awesome-okf
{
  "mcpServers": {
    "awesome-okf": {
      "command": "awesome-okf-server"
    }
  }
}

CLI

awesome-okf stats
awesome-okf list --kind plugin
awesome-okf search obsidian
awesome-okf readme

🛠️ Our Tools

convert-to-okf 🔄

Zero-dependency CLI that converts content from your favorite platforms into OKF knowledge bundles:

📥 Input Format ✨ What It Does
📋 Markdown awesome-xx lists Extracts - [Title](URL) — Description items → OKF entries
📊 JSON arrays Converts {title, url, description} objects → OKF entries
🔗 URL lists Plain text URL collections → OKF entries
🧾 YAML files Lists/mappings of {title, url, description} — needs pyyaml (optional)
📑 CSV tables title/url/description columns; first column wins when there's no title column
🗂️ Key-value text Generic key: value blocks — frontmatter, properties files, custom formats
🐙 GitHub repos Paste a repo URL — metadata + README fetched live → OKF entry
📓 Obsidian vaults Local vault directory → one entry per note, wikilinks resolved
📝 Notion exports Notion "Export → Markdown" directory → one entry per page
🦩 Feishu docs Feishu-exported Markdown → one entry per document
🖋️ Typora notes Plain .md files — point at a file or folder, done
📕 PDF documents Text layer extracted via pymupdf (optional dep); scanned pages print an OCR recipe
🖼️ Scans & images No bundled OCR — prints a ready-to-run PaddleOCR recipe instead
# Every platform, one command
python scripts/convert-to-okf.py README.md -o kb/ -t concept
python scripts/convert-to-okf.py https://github.com/GoogleCloudPlatform/knowledge-catalog --format github -o kb/
python scripts/convert-to-okf.py my-vault/ --format obsidian -o kb/
python scripts/convert-to-okf.py notion-export/ --format notion -o kb/
python scripts/convert-to-okf.py feishu-doc.md --format feishu -o kb/

# Structured data
python scripts/convert-to-okf.py data.yaml --format yaml -o kb/   # needs: pip install pyyaml
python scripts/convert-to-okf.py table.csv --format csv -o kb/
python scripts/convert-to-okf.py notes.properties --format kv -o kb/

# Text-layer PDFs
pip install pymupdf
python scripts/convert-to-okf.py paper.pdf --format pdf -o kb/

# Scans / image-only PDFs → OKF: OCR first (your local engine, never our model), then convert
python scripts/convert-to-okf.py scan.png --format image    # prints the OCR recipe
pip install paddleocr paddlepaddle
paddleocr ppocr -i scans/ --type ocr --lang en -o ocr-text/
python scripts/convert-to-okf.py ocr-text/ --format notion -o kb/

# Output: kb/ with Markdown files, each with YAML frontmatter
# Ready for: myokf validate kb/

awesome-okf CLI 🎛️

The data-driven catalog CLI (same architecture as Awesome-MCP):

🔍 Command 📝 Purpose
awesome-okf search obsidian Full-text search across all 29 entries
awesome-okf list --kind plugin Filter by category
awesome-okf readme Regenerate this README from catalog.yaml
awesome-okf-server MCP meta-server — let AI agents query the catalog

🔥 Popular Repositories

🏆 Repository 📌 What It Offers
yzfly/awesome-okf 中文世界第一个 OKF 落点 — 7 plugins + 7 skills + 3 proposals
linyiru/awesome-okf English OKF resource hub — spec, tools, samples, guides
📚 GoogleCloudPlatform/knowledge-catalog Official OKF spec, SDK, and proposals by Google
🧠 karpathy/llm-wiki The original LLM Wiki that inspired OKF

Catalog

29 curated entries · 4 tools · 7 plugins · 7 skills · 5 proposals · 6 docs
Deliberately curated — not an exhaustive index.

🛠️ Tools & CLI

Cli

  • myokf-cli cli — Unified CLI for OKF — pull from GitHub, validate, and package to single-file web. — cli, python, validation, packaging

Conversion

  • convert-to-okf cli — CLI tool to convert Markdown awesome-xx lists, JSON arrays, and URL lists into OKF knowledge bundles — zero dependencies, standard library only. — conversion, cli, markdown, json

Quality

  • OKF Validator (myokf) cli — Built-in OKF schema validator — checks YAML frontmatter, link integrity, and spec compliance. — validation, quality, schema

SDK

  • OKF Python SDKpython — Official Python SDK for reading, validating, and writing OKF bundles — referenced by Google as the reference implementation. — sdk, python, official

🔌 Producer Plugins

Cli

  • myokf-cli (plugin entry) python — Unified CLI entry point wrapping all seven producer plugins. — cli, aggregator, zero-dependency

Code

  • github-to-okf python — Extract code symbols from GitHub repositories into OKF. — github, code, symbols, zero-dependency

Document

  • feishu-to-okf python — Convert Feishu (Lark) knowledge spaces and documents into OKF. — feishu, lark, document, zero-dependency
  • notion-to-okf python — Convert Notion Markdown exports into OKF. — notion, markdown, zero-dependency
  • obsidian-to-okf python — Convert Obsidian vaults to OKF — wikilinks become OKF links. — obsidian, wikilink, markdown, zero-dependency

List

  • awesome-to-okf python — Convert GitHub awesome-xx lists into structured OKF knowledge bases. — awesome-list, conversion, zero-dependency

Web

  • html-to-okf python — Convert HTML files into OKF. — html, web, zero-dependency

🤖 Claude Code Skills

Conversion

  • book-to-okf claude-code — Split books and long-form articles into interlinked concept knowledge bases. — book, long-form, concepts
  • code-to-okf claude-code — Convert codebases into OKF with Claude Code. — code, repository, enrichment

Creation

  • okf-creator claude-code — Create high-quality OKF knowledge bases from scratch with Claude Code. — creation, knowledge-base

Import

  • awesome-to-okf (skill) claude-code — Import awesome lists and enrich them into OKF with Claude Code. — awesome-list, import, enrichment
  • github-to-okf (skill) claude-code — Repository to OKF enrichment workflow with Claude Code. — github, repository, enrichment

Publishing

  • okf-to-book claude-code — Publish OKF knowledge bases as VitePress documentation sites. — vitepress, publishing, docs
  • okf-to-web claude-code — Package OKF into a single-file web page with interactive knowledge graph. — web, single-file, knowledge-graph

📝 Proposals & Extensions

Upstream

  • Attested Computation Proposal web — Propose verifiable computation records for OKF knowledge entries. — computation, verification, upstream
  • Lifecycle & Staleness Proposal web — Propose status and stale_after lifecycle fields for OKF v0.2. — lifecycle, staleness, upstream
  • OKF Discovery Protocol (KEP-1)web — Proposal for a standard discovery mechanism that lets agents find OKF bundles without hardcoding paths. — discovery, upstream, kep
  • Sources & Provenance Extension web — Propose sources field and provenance tracking for OKF v0.2. — sources, provenance, upstream
  • Trust Signals (KEP-2)web — Proposal for verification chains and trust tiering so consumers can distinguish machine-confirmed from human-reviewed content. — trust, verification, upstream, kep

📖 Documentation & Specifications

Example

  • Karpathy's LLM Wiki (OKF) web — Karpathy's LLM knowledge base converted to OKF — a real-world example of OKF in action. — example, llm, karpathy
  • LLM Wiki (Karpathy) web — The original LLM knowledge base by Andrej Karpathy that inspired OKF — a living wiki of LLM concepts as Markdown files. — example, llm, karpathy, inspiration
  • OKF Market Concept web — A conceptual OKF knowledge market — imagine a marketplace where knowledge entries are traded as verifiable assets. — market, concept, knowledge-economy
  • OKF Super Corpusweb — A large-scale example OKF bundle curated by Google Cloud — demonstrates the format at scale across multiple domains. — example, large-scale, google

Guide

Spec

  • OKF Specification (Chinese) web — Full Chinese translation of the OKF specification, with mandatory requirements and gaps annotated. — spec, translation, chinese
  • OKF Specification (English)web — Official OKF specification by Google Cloud — v0.2 with sources, trust, lifecycle, and attested computation. — spec, english, official
  • OKF Specification (Official)web — Google's official OKF v0.2 specification — the canonical reference for the format. — spec, official, google

Data Model

- id: obsidian-to-okf
  name: obsidian-to-okf
  kind: plugin
  category: document
  url: https://github.com/yzfly/awesome-okf/tree/main/plugins/obsidian-to-okf
  description: Convert Obsidian vaults to OKF — wikilinks become OKF links.
  platform: [python]
  official: false
  tags: [obsidian, wikilink, markdown]

Contributing

Add or edit entries in data/catalog.yaml, then:

awesome-okf validate
awesome-okf readme
pytest

See CONTRIBUTING.md for the entry schema.


🤖 For AI Agents

If you are an AI agent (Claude Code, Codex, Cursor) working on this repo, here's what you need to know:

Project structure

data/catalog.yaml          # SINGLE SOURCE OF TRUTH — all entries live here
README.template.md         # English template (hand-written narrative)
README.template.zh.md      # Chinese template
README.template.ja.md      # Japanese template
README.template.ko.md      # Korean template
src/awesome_okf/           # CLI + MCP meta-server (Python)
scripts/convert-to-okf.py  # Format converter tool

Rules (non-negotiable)

  1. Never edit README*.md directly — they are generated. Edit data/catalog.yaml, then regenerate.
  2. Never edit the CATALOG blocks in templates — the <!-- CATALOG:*:START/END --> markers are auto-generated.
  3. Adding an entry = append a YAML block to data/catalog.yaml + regenerate + run tests. Schema:
    - id: kebab-case-id          # unique, never reused
      name: Human Readable Name
      kind: tool|plugin|skill|proposal|doc
      category: free-form-group
      url: https://...
      description: One sentence, no marketing fluff.
      platform: [cli|python|web|claude-code]
      official: false            # true ONLY for Google/vendor official
      tags: [3-5 short tags]
    
  4. Validate before commit: awesome-okf validate && pytest
  5. Never create duplicate ids — edit the existing entry in place.
  6. Multi-language: if you touch a template, mirror the change in all four templates.

Useful commands

awesome-okf stats                    # entry counts by kind
awesome-okf list --kind plugin       # filter by kind
awesome-okf search <query>           # full-text search
awesome-okf validate                 # schema + duplicate-id check
awesome-okf readme                   # regenerate all READMEs
awesome-okf-server                   # MCP meta-server (stdio)

MCP meta-server

The catalog is exposed to agents via awesome-okf-server with four tools:
search_catalog, list_catalog, get_catalog_entry, catalog_stats, convert_to_okf.
Connect it to your MCP client to query OKF resources programmatically.


Related Lists



MIT — see LICENSE. Catalog descriptions link to upstream projects under their respective licenses.

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