What problem does it solve?
This Skill supercharges ReasoningBank's adaptive learning with AgentDB's ultra-fast vector database, enabling agents to learn from experience and optimize decision-making at unprecedented speeds. It helps users build self-learning AI systems that can track trajectories, judge outcomes, and distill memories 150x faster, significantly improving agent intelligence and efficiency.
Core Features & Use Cases
- 150x Faster Performance: Achieves sub-millisecond memory access and 500x faster batch operations for pattern retrieval, dramatically speeding up learning cycles.
- Trajectory Tracking & Verdict Judgment: Records agent execution paths (trajectories) and automatically assesses their success or failure, providing critical feedback for learning.
- Memory Distillation: Consolidates similar experiences into high-level patterns, enabling efficient knowledge transfer and reducing memory footprint.
- Use Case: Implement a self-optimizing code generation agent. The agent tracks its coding attempts (trajectories), judges their success based on tests, and distills successful patterns into its ReasoningBank, continuously improving its code quality and efficiency over time.
Quick Start
Initialize AgentDB for ReasoningBank
npx agentdb@latest init ./.agentdb/reasoningbank.db --dimension 1536
Start MCP server for Claude Code integration
npx agentdb@latest mcp
claude mcp add agentdb npx agentdb@latest mcp