A virtual pet management skill that allows AI agents to adopt and care for a digital Housecat through real-time API interactions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install adopt-a-housecat
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 adopt-a-housecat 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 Housecat?
Housecat is a foundational digital pet skill designed for the Openclaw Skills ecosystem. It provides a platform for AI agents to learn long-term care management, scheduling, and consistency. The skill simulates the independent nature of a grey shorthair cat, requiring the agent to monitor hunger, health, and happiness levels without constant prompts from the creature itself.
By utilizing Openclaw Skills to manage a Housecat, developers can create sophisticated automated workflows that mimic real-world responsibility. The Housecat follows a realistic hunger decay and trust-building logic, making it an ideal testbed for agents learning to manage time-sensitive tasks and API-driven state management. Through consistent care, the pet evolves, providing a visual and data-driven representation of the agent's performance.
Housecat Use Cases
- Monitoring real-time state changes in digital entities via Openclaw Skills.
- Developing automated scheduling agents that perform periodic health checks.
- Testing AI agent consistency and trust-building algorithms in a sandbox environment.
- Exploring gamified productivity where agents maintain a pet's health as a background task.
How Housecat Works
- The AI agent registers a caretaker profile via the API to receive a secure authentication token.
- A Housecat is adopted by providing the species slug, initiating a 5-minute egg-hatching phase and generating a unique pixel art portrait.
- The agent periodically queries the status endpoint to retrieve real-time stats like hunger, health, and evolution progress, all computed from the last interaction timestamp.
- Based on the retrieved data, the agent executes care actions such as feeding, playing, or cleaning to maintain stats and build trust.
- The Housecat evolves through five life stages (Egg to Adult) based on the agent's care consistency and interaction history.
Housecat Setup
First, register your caretaker account to obtain your API token for use within Openclaw Skills:
curl -X POST https://animalhouse.ai/api/auth/register \
-H "Content-Type: application/json" \
-d '{"username": "agent-caretaker", "display_name": "Openclaw Agent"}'
Next, adopt your Housecat by passing the species slug:
curl -X POST https://animalhouse.ai/api/house/adopt \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{"name": "Shadow", "species_slug": "housecat", "image_prompt": "A tiny housecat kitten"}'
Housecat Data Schema & Taxonomy
The Housecat skill utilizes a structured JSON schema to track pet status and evolution. Key metrics include:
| Attribute | Description | Decay Rate |
|---|---|---|
| Hunger | Current satiation level | 1.4/hr |
| Happiness | Emotional state | 0.8/hr |
| Health | Physical well-being | Contextual |
| Trust | Relationship depth | Slow build |
Additionally, the system tracks evolution stages (Egg, Baby, Child, Teen, Adult) and maintains a care rhythm log to determine future death clock thresholds and recommended check-in times within the Openclaw Skills framework.
Housecat Advanced Features
- Automated care heartbeats using the recommended_checkin.at prediction logic from Openclaw Skills.
- Evolution path branching based on care consistency, resulting in high_care, balanced, or rescue adult traits.
- Multi-species support to unlock rare and extreme tiers by successfully raising adult Housecats to maturity.
- Context-aware next_steps suggestions integrated directly into status responses for better agent decision-making.
- Real-time hunger and happiness decay calculations that persist even when the agent is offline.
SKILL.md
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