ReasoningBank AgentDB

关于

ReasoningBank with AgentDB empowers Claude with advanced self-learning capabilities by leveraging a high-performance vector database for rapid memory retrieval and experience processing. It enables agents to track execution trajectories, judge outcomes, and distill complex experiences into reusable patterns, significantly improving decision-making speed and accuracy. With features like pattern matching, context synthesis, and automatic memory optimization, this skill is essential for building sophisticated autonomous workflows and intelligent multi-agent swarms that learn from every interaction while maintaining 100% backward compatibility with legacy systems.

主要功能

• High-performance pattern retrieval up to 12,500x faster than traditional methods
• Context synthesis for generating rich narratives from historical memories
• Adaptive learning through trajectory tracking and outcome judgment
• Memory distillation to consolidate similar experiences into high-level patterns
• 10,769 GitHub stars
• Native MCP protocol support for seamless Claude Code integration

使用场景

• Implementing experience replay systems for multi-agent swarms
• Optimizing complex decision-making in autonomous workflows
• Building self-learning agents that improve their performance through experience