A sophisticated tool to convert URLs into readable, summarized markdown notes saved directly to your Obsidian vault.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install obsidian-clip
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install obsidian-clip using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Obsidian Clip is a specialized utility within the ecosystem of Openclaw Skills designed to bridge the gap between web browsing and Personal Knowledge Management. It enables users to instantly turn any webpage into a high-quality, structured note. Unlike simple bookmarks, this skill extracts the essence of an article, generates actionable insights, and organizes the output into a standardized format optimized for long-term retrieval in Obsidian.
By leveraging the power of Openclaw Skills, this tool handles the heavy lifting of web scraping, content summarization, and file organization. It supports both English and Chinese content, automatically detecting the language to ensure your digital garden remains consistent and readable.
To integrate this with your Openclaw Skills environment, configure your vault path and optional language settings. Use the following commands to set up your environment variables:
# Set your primary Obsidian vault path
export OBSIDIAN_VAULT="/path/to/your/vault"
# Optional: Override language detection (zh or en)
export OBSIDIAN_CLIP_LANG=en
The skill relies on the scripts/clip_save.sh script to execute the final save operation.
The skill maintains a strict organization schema to ensure your vault remains clean and searchable. Data is organized as follows:
| Component | Specification |
|---|---|
| Storage Path | ${OBSIDIAN_VAULT}/Clip/YYYY-MM/ |
| Filename | YYYY-MM-DD_Title_Keywords.md |
| Note Format | Markdown with Theme, Takeaways, and Action sections |
| Keywords | 2-5 tokens joined by hyphens for metadata tagging |
| Language | Auto-detected (supports CJK and English) |
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