A markdown-first knowledge management skill that automates the transition from raw source material to a structured, interlinked Obsidian wiki.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install duru-obsidian-kb
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install duru-obsidian-kb using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Duru Obsidian KB?
Duru Obsidian KB is a professional-grade tool designed for developers and researchers who want to maintain an auditable, local-first knowledge repository. Leveraging the power of Openclaw Skills, this tool implements a robust workflow that ingests content from web articles, arXiv papers, GitHub repositories, and local files into a standardized directory structure. By prioritizing deterministic file generation over chat-only responses, it ensures your data remains portable and easy to diff within the Obsidian ecosystem.
The system follows a rigorous raw-to-wiki-to-output pipeline, ensuring that every piece of information is accounted for in a manifest before being synthesized into concept pages or research briefs. This makes it an essential asset for those using Openclaw Skills to manage complex information environments without losing the provenance of their source material.
Duru Obsidian KB Use Cases
- Automating the collection of research papers and web articles into a local markdown wiki.
- Compiling structured notes from multiple GitHub repositories for technical documentation.
- Generating research briefs or Marp presentation slides from a compiled knowledge base.
- Running consistency and health checks across large-scale personal knowledge management systems.
- Extracting and organizing data from spreadsheets and local files into interlinked Obsidian pages.
How Duru Obsidian KB Works
- Initialize the knowledge base structure including raw storage, wiki directories, and configuration manifests.
- Ingest source material from URLs or local paths, detecting content types such as articles, PDFs, or repositories.
- Normalize metadata into a central manifest and extract text using deterministic methods and safety scans.
- Route content to the appropriate repository using rule-based logic or local model hooks.
- Build or refresh the wiki by creating source pages, concept pages, and automated backlinks.
- Generate specific outputs like research memos or presentation decks based on the synthesized knowledge.
- Execute linting scripts to validate structural integrity and metadata consistency.
Duru Obsidian KB Setup
To get started with this skill, initialize your knowledge base using the provided script:
python3 scripts/kb_init.py --root /path/to/your/kb
To add new content and trigger the automated ingestion and build pipeline, use the unified entrypoint:
python3 scripts/kb_add.py --root /path/to/your/kb --source "https://arxiv.org/abs/xxxx.xxxxx"
Duru Obsidian KB Data Schema & Taxonomy
The skill organizes data within a designated root folder using a strict taxonomy to ensure compatibility with Obsidian and version control systems:
| Directory | Description |
|---|---|
raw/ |
Stores original source material (articles, papers, repos, files). |
wiki/ |
Contains the compiled knowledge (concepts, sources, indexes). |
outputs/ |
Stores generated deliverables like markdown briefs and Marp slides. |
manifest.json |
The central registry of all ingested content and metadata. |
config.json |
Local configuration for paths and routing rules. |
Duru Obsidian KB Advanced Features
- Multi-repo routing using rules-first scoring and local-model hooks for high-precision content categorization.
- Automated chart generation from CSV and XLSX data, integrating visual artifacts directly into wiki concept pages.
- Integration with prompt-shield-lite for security-focused extraction and noise detection in web content.
- Deterministic index generation for timelines, tags, and concepts to maintain a navigable knowledge graph.
- Smoke testing and health check scripts to ensure the stability of the entire Openclaw Skills automation pipeline.
SKILL.md
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