A professional household organization tool for generating printable stain tracking tags, sorting labels, and laundry workflow checklists.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install laundry-stain-prep-tags
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 laundry-stain-prep-tags using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Laundry Stain Prep Tags skill is a specialized organizational framework designed to prevent permanent fabric damage by ensuring stained items are identified before they hit the wash. As a standout entry in the Openclaw Skills library, this tool generates high-visibility tags and labels that bridge the communication gap between discovering a stain and the actual laundry cycle.
By providing a structured way to mark stain locations, owners, and specific care requirements, the skill streamlines household management. It focuses on administrative organization—such as creating do-not-dry flags and hamper lane labels—rather than offering risky chemical advice, making it a safe and essential utility for busy households, sports teams, or uniform management.
To utilize this organizational workflow within your environment, simply invoke the skill through your AI agent interface. No complex installation is required as it is a prompt-based logic set.
# Example command to initiate the workflow
openclaw run laundry-stain-prep-tags --prompt "Generate tags for kids sports gear"
The skill organizes laundry metadata into the following structured components:
| Component | Data Fields Included |
|---|---|
| Stain Prep Tags | [ITEM], [OWNER], [STAIN TYPE], [LOCATION], [DATE], [ACTION] |
| Hamper Labels | Wash Now, Pretreat, Do Not Dry, Delicate, Ask Owner, Repair |
| Handoff Points | Hamper, Laundry Room, Washer Top, Drying Rack, Mudroom |
| Checklists | Collection steps, Care label verification, Tag removal protocols |
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