Whisker (Litter-Robot cards)
Open Source

Whisker (Litter-Robot cards)

2026·Open Source / Community

Overview

Open-source Lovelace dashboard cards for the Whisker and Litter-Robot integration in Home Assistant, giving pet owners clear visibility into litter status, cycles, and device health without leaving their smart-home UI. Built with TypeScript for the frontend stack, distributed via HACS, and maintained under the homeassistant-extras GitHub organization for easy install and updates.

README

Whisker Card

Litter-Robot status and controls in a single Lovelace card

Whisker Card preview

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Overview

Whisker Card is a custom Lovelace card for Home Assistant that shows your Litter-Robot at a glance, using the official Litter-Robot integration (litterrobot).

Documentation

Full documentation is available at: homeassistant-extras.github.io/whisker

Quick Start

type: custom:whisker-card
device_id: YOUR_DEVICE_ID

Replace YOUR_DEVICE_ID with the id from the device page in Home Assistant, or use the UI editor to pick the device.

Installation

HACS (recommended)

HACS

  1. Open HACS in Home Assistant.
  2. Open the menu → Custom repositories.
  3. Add https://github.com/homeassistant-extras/whisker and category Dashboard.
  4. Install Whisker Card and restart if prompted.

Manual installation

  1. Download whisker.js from the latest release (dist/whisker.js).
  2. Copy to www/community/whisker/.
  3. Add the Lovelace resource — see Installation for configuration.yaml details.

Contributing

License

This project is licensed under the MIT License. See the LICENSE file.

Acknowledgments

contributors

ko-fi

Project Roadmap

  • Litter-Robot device discovery via translation_key mapping
  • Visual card — status, gauges, pet weight, last seen
  • Tap / hold actions on status icons (cycle / reset vs more-info)
  • Controls dialog with native entity rows
  • Lovelace card editor (device selector + title)
  • Automated tests (Mocha)
  • Gauge percentages — optional percentage labels on litter/waste gauges - thanks reddit!
  • Customizable footer — choose footer metrics and order - thanks @alicia86
  • Model-aware artwork — auto-detects Litter-Robot model - thanks @adude007