A comprehensive memory layer that gives AI agents personality, long-term learning, and secure credential storage.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install brain-v3-skill
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 brain-v3-skill 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 clawbrain?
clawbrain is a specialized personal AI memory system developed for the Openclaw Skills ecosystem. It transforms standard AI interactions into personalized experiences by providing agents with an evolving soul consisting of six distinct personality traits: humor, empathy, curiosity, creativity, helpfulness, and honesty. Beyond simple chat history, it manages deep user profiles and conversation states to ensure every interaction is contextually relevant and emotionally intelligent.
This skill serves as the central nervous system for agents, enabling them to learn user preferences, detect real-time moods, and securely store sensitive data through an encrypted secrets module. Whether you are building a simple assistant or a complex autonomous agent, clawbrain provides the infrastructure needed for persistent memory and personality bonding.
clawbrain Use Cases
- Creating persistent AI personas that maintain consistent personality traits across sessions
- Building empathetic customer support agents that adapt their tone based on detected user mood
- Securely managing and retrieving API keys or credentials within an agent workflow
- Developing personalized learning assistants that remember user interests and communication styles
- Implementing automated session summarization to maintain long-term context without token bloat
How clawbrain Works
- The system triggers a gateway:startup hook to initialize the memory brain and detect the preferred storage backend.
- It loads existing memories and user profiles associated with a specific agent ID into the current session context.
- Throughout the interaction, the skill monitors incoming messages to detect user intent, mood, and preferences.
- When a new session is initiated, the system automatically summarizes the previous conversation and updates the long-term memory store.
- All sensitive information is handled through a dedicated encryption layer using Fernet keys before being written to the database.
clawbrain Setup
To install this skill, use the following commands in your terminal:
# Install the package with all dependencies
pip install clawbrain[all]
# Run the interactive setup to configure keys and hooks
clawbrain setup
# Securely backup your encryption key
clawbrain backup-key --all
# Restart your agent service to apply changes
sudo systemctl restart clawdbot
You can further customize the installation by setting environment variables like BRAIN_AGENT_ID or BRAIN_POSTGRES_HOST in your service configuration.
clawbrain Data Schema & Taxonomy
The skill organizes information into several key data structures to provide a rich context for Openclaw Skills:
| Data Component | Description |
|---|---|
| User Profile | Tracks persistent data like names, interests, and preferred communication styles. |
| Soul Traits | A set of 6 evolving metrics that define the agent's personality and behavior. |
| Conversation State | Real-time tracking of user mood (e.g., happy, frustrated) and interaction intent. |
| Encrypted Secrets | Secure storage for API keys and credentials, decrypted only at runtime. |
| Learning Insights | Derived data points from user corrections and repeated interactions. |
clawbrain Advanced Features
- Multi-backend storage support with automatic failover from PostgreSQL to local SQLite
- Secure Fernet encryption for sensitive data with CLI-based key management and QR backups
- Real-time mood detection and intent classification for dynamic response adjustment
- Automated hooks for service startup and session clearing to ensure memory consistency
- High-concurrency support using Redis for production-grade agent deployments
SKILL.md
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