ReasoningBank with AgentDB

What problem does it solve?

This Skill supercharges AI adaptive learning by integrating ReasoningBank with AgentDB's ultra-fast vector database (150x-12,500x faster). It enables agents to learn from experiences, judge outcomes, distill memories, and optimize decision-making with unparalleled speed and efficiency.

Core Features & Use Cases

• Trajectory Tracking: Record and analyze agent execution paths and outcomes.
• Verdict Judgment: Automatically assess the success of agent trajectories based on past patterns.
• Memory Distillation: Consolidate similar experiences into high-level, reusable patterns.
• Use Case: Implement a self-learning agent that optimizes API endpoints. It tracks successful optimization trajectories, judges new attempts against these, and distills common patterns (e.g., "For N+1 queries: add eager loading, then cache") for future use.

Quick Start

Initialize AgentDB for ReasoningBank and then use the API to store a successful experience about optimizing database queries.