Archive is an intelligent content preservation skill that captures full snapshots of articles, videos, and papers with semantic search and proactive context resurfacing.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install archive
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 archive using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Archive goes beyond simple bookmarking by creating permanent, intelligent snapshots of external content within your local environment. Unlike traditional link savers, this tool for Openclaw Skills extracts full text, generates concise summaries, and categorizes data based on your specific research intent and history.
By focusing on the why behind every saved item, Archive ensures that your digital library remains actionable. It integrates deeply into your workflow to resurface relevant past research exactly when you need it, preventing information silos and making your stored knowledge a living part of your development process.
To begin using Archive with Openclaw Skills, initialize the required directory structure on your local machine:
mkdir -p ~/archive/items ~/archive/projects
touch ~/archive/memory.md ~/archive/index.md ~/archive/history.md
Ensure your agent has the necessary permissions to read and write to the ~/archive/ path for seamless content logging.
Archive organizes information in a tiered Markdown-based system for maximum portability:
| File/Folder | Purpose |
|---|---|
memory.md |
Recent items (up to 100 lines) for quick context access. |
index.md |
A master directory of topics and tags for easy navigation. |
items/ |
Individual Markdown files for every archived resource containing full content and metadata. |
projects/ |
Specialized collections grouped by specific project names. |
history.md |
A log of search queries and access patterns to improve future suggestions. |
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