An intelligent knowledge management assistant that automates the organization, retrieval, and maintenance of Obsidian-based wikis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install llm-wiki-skill
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 llm-wiki-skill 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 LLM-Maintained Knowledge Wiki (llmwiki)?
The llmwiki skill is a comprehensive knowledge management solution designed for users who want the benefits of a curated wiki without the manual overhead of bookkeeping. By utilizing Openclaw Skills, this tool takes over the structural management of your data, allowing you to focus on high-level curation and learning. It operates directly within Obsidian vaults, ensuring your data remains local and accessible while benefiting from AI-driven organization.
At its core, the skill functions as a router that delegates specific tasks—like extracting insights from new sources or auditing existing content for stale information—to specialized sub-skills. This modular approach makes it one of the most robust Openclaw Skills for personal knowledge management (PKM) and research workflows.
LLM-Maintained Knowledge Wiki (llmwiki) Use Cases
- Build a compounding personal knowledge base from fragmented Obsidian notes.
- Automatically capture and format insights from web articles or technical documentation.
- Retrieve synthesized answers from your past research history without re-reading raw files.
- Maintain a healthy vault by identifying orphans, stubs, and broken links automatically.
How LLM-Maintained Knowledge Wiki (llmwiki) Works
- The user initiates a command via the /llmwiki trigger followed by a sub-command like ingest, query, or health.
- The skill parses the arguments to determine the user's intent and delegates the task to the appropriate sub-module.
- For ingestion, the AI analyzes a source (URL or file) and generates structured content within the _wiki/ directory.
- For queries, the agent searches the existing wiki files and synthesizes a concise answer based on documented evidence.
- For health checks, the skill audits the file structure and metadata to ensure the wiki remains interconnected and up to date.
LLM-Maintained Knowledge Wiki (llmwiki) Setup
To activate this skill within your environment, ensure you have the Openclaw Skills framework initialized in your Obsidian vault. You can verify the installation and check the current status of your wiki by running the health command:
/llmwiki health
No additional complex configuration is required as the skill automatically maps to the _wiki/ folder in your current working directory.
LLM-Maintained Knowledge Wiki (llmwiki) Data Schema & Taxonomy
The skill organizes information using a structured taxonomy to ensure compatibility with both human readers and AI agents. Information is primarily stored in the following manner:
| Data Point | Description |
|---|---|
| Directory | All generated content is stored in the _wiki/ root folder. |
| Page Format | Standardized Markdown with specific frontmatter for metadata. |
| Metadata | Includes source origins, creation timestamps, and relationship tags. |
| Sub-skills | Modular logic found in llmwiki-ingest, llmwiki-query, and llmwiki-health. |
LLM-Maintained Knowledge Wiki (llmwiki) Advanced Features
- Multi-source ingestion supporting local Markdown files, remote URLs, or general text topics.
- Context-aware synthesis that pulls from across your entire wiki to answer complex questions.
- Automated health auditing to prevent information decay and broken internal references.
- Seamless integration with Obsidian for a high-quality visual representation of the LLM-managed data.
SKILL.md
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