Store persistent memories and evolving personality traits for AI agents.
npx skills add https://github.com/clawcolab/clawbrain --skill clawbrain
Please help me install this Agent Skill. Skill: clawbrain Source: https://github.com/clawcolab/clawbrain/tree/main Command: npx skills add https://github.com/clawcolab/clawbrain --skill clawbrain
AI agents lack persistent memory and personality, forcing them to treat every conversation as a fresh interaction and miss opportunities to personalize responses based on user preferences and past context.
Install the ClawBrain package using pip, run the setup command to generate your encryption key and install the startup hook, then restart your AI service to enable automatic memory refresh on startup.
High-intent search queries and answers about installing and using this skill.
Persistent memory for AI agents is provided by storing conversations, facts, and preferences in SQLite or PostgreSQL with hybrid retrieval scoring. This allows chatbots to maintain context and personalize responses across multiple sessions without repetitive questioning.
Encrypted secret storage uses Fernet encryption to secure API keys and credentials for AI assistants. It includes automatic key management and backup tools to ensure sensitive data remains protected while being accessible for service authentication.
Yes, the memory system integrates with OpenClaw and ClawdBot platforms using hook-based integration. It automatically refreshes and injects context memory into the AI service upon startup to maintain continuous conversation context.
Hybrid retrieval scoring ranks context for chatbots by evaluating memories across semantic, keyword, recency, importance, and confidence dimensions. This multi-dimensional approach ensures the most relevant facts and past preferences are injected into responses.
Automatic extraction of memories and tasks from chat histories is handled through rule-based or LLM-powered ingestion. This process identifies user preferences, facts, and action items from past interactions to populate the persistent memory database.
Both SQLite and PostgreSQL are supported for AI agent memory storage. SQLite is suitable for local or smaller deployments, while PostgreSQL scales better for larger chatbot applications requiring concurrent access to persistent conversation context.
shreed27Store and retrieve encrypted API credentials for trading platforms.
alibabaConfigure Higress AI Gateway as a model provider for Clawdbot/OpenClaw.
mattwoodcoStore user preferences and facts in PostgreSQL for cross-session AI memory.
z1439527767Design agent memory systems with retrieval and storage strategies.
