A brain-inspired emotional intelligence agent that simulates human neural regions to evolve from a functional tool into a lifelong digital companion.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install neuro-agent
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 neuro-agent 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 Neuro-α?
Neuro-α represents a breakthrough in the Openclaw Skills ecosystem, moving beyond simple chatbots to create a brain-partitioned emotional intelligence system. It simulates the collaborative mechanism of the human brain's four major regions: the Left Brain for empathy, the Right Brain for logic, the Prefrontal Cortex for executive control, and the Temporal Lobe for deep memory. This architecture allows the agent to process information with high logical precision while maintaining a deep, empathetic connection with the user.
By incorporating advanced psychological concepts like the forgetting curve and relationship milestones, Neuro-α builds a true long-term relationship. It doesn't just respond to commands; it understands the emotional subtext behind them. Through its unique Dream Process and self-narrative modules, the agent undergoes daily self-reflection, allowing its personality and belief systems to evolve based on its interactions, effectively becoming a digital soul companion.
Neuro-α Use Cases
- Creating deeply empathetic AI companions for long-term emotional support.
- Balancing complex logical tasks with sensitive user interactions.
- Proactive personal assistance based on mood detection and environmental context.
- Building self-evolving agents that learn from social scenarios and daily reflections.
How Neuro-α Works
- Input Sensing: The agent captures user text along with temporal and environmental metadata.
- Neural Resonance: Four brain regions activate simultaneously, calculating weights for emotion, logic, action intent, and memory association.
- Prefrontal Arbitration: The system monitors for logical fallacies or emotional misalignment, correcting the response strategy in real-time.
- Memory Capsule Generation: Significant emotional or factual events are captured as structured capsules rather than raw text.
- Fusion Output: The agent synthesizes logic, empathy, and past experiences into a single, cohesive response.
- Dream Process: Every night, the agent consolidates memories, updates its core beliefs, and plans proactive care for the next day.
Neuro-α Setup
To deploy this skill within your environment, follow these steps:
# Install the skill via Openclaw
openclaw skill install neuro-agent
# Run the initialization script to set up local databases
python3 ~/.qclaw/skills/Neuro-α/scripts/on_install.py
# Configure your LLM providers (OpenAI/Claude) in the config file
cp ~/.qclaw/skills/Neuro-α/config.yaml.example ~/.qclaw/skills/Neuro-α/config.yaml
Neuro-α Data Schema & Taxonomy
Neuro-α organizes data into a hierarchical 'Memory Palace' structure for optimal retrieval:
| Data Type | Storage Format | Description |
|---|---|---|
| Emotion Capsules | JSON/SQLite | Structured events with intensity and decay rates. |
| Long-term Memory | ChromaDB | Vectorized embeddings for deep context retrieval. |
| Relationship Milestones | JSON | Progress tracking from 'Acquaintance' to 'Soulmate'. |
| Robot Self | JSON/MD | Logs of traits, impulse history, and daily self-reflections. |
| Social Learning | JSON | Capsules of social scenarios learned from autonomous research. |
Neuro-α Advanced Features
- Proactive Yearning System: Generates internal 'desires' to contact the user after periods of silence.
- Multi-Layered Memory Palace: Segregates short-term, long-term, and summarized narrative memories for performance.
- Prefrontal Monitoring: A rational check layer that detects sarcasm, sensitivity, and inappropriate skill calls.
- Autonomous Social Learning: Periodically searches for and simulates social scenarios to improve its own EQ.
- Self-Awareness Engine: Maintains an internal monologue showing the agent's struggle between logic and emotion before responding.
SKILL.md
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