Agentdb Memory Patterns
Skill Verified ActiveImplement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
To enable developers to build more sophisticated and stateful AI agents by providing efficient and robust memory management capabilities.
Features
- Persistent memory patterns for AI agents
- Session memory and long-term storage
- Pattern learning and context management
- AgentDB integration for high-performance vector storage
- CLI tools for database management and MCP server setup
Use Cases
- Building stateful AI agents
- Developing intelligent chat systems
- Creating agents that learn from interactions
- Managing context across long agent sessions
Non-Goals
- Replacing core LLM functionality
- Providing a full-fledged agent framework without AgentDB integration
- Handling real-time data streaming beyond conversation history
Installation
npx skills add ruvnet/rufloRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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