What problem does it solve? Agents that cannot learn from past executions repeat mistakes and rediscover solutions. This Skill provides ReasoningBank patterns on AgentDB's vector database so agents can store experiences, judge outcomes, distill memories, and retrieve relevant patterns for better decisions. ## Core Features & Use Cases - Trajectory Tracking & Verdict Judgment: Record agent execution paths with outcomes and judge new trajectories against similar past successes. - Memory Distillation: Consolidate similar experiences into high-level patterns with confidence scores and success rates. - Reasoning Modules: Use PatternMatcher, ContextSynthesizer, MemoryOptimizer, and ExperienceCurator for retrieval, synthesis, and automatic consolidation. - Use Case: A coding agent stores each optimization attempt as a trajectory; before the next task it retrieves similar past patterns via embedding search and reuses the approach with the highest success rate. ## Quick Start Initialize an AgentDB database with npx agentdb@latest init, then use the createAgentDBAdapter API to insert and retrieve experience patterns with embeddings.
