What is ReasoningBank?

ReasoningBank is an adaptive learning pattern that allows AI agents to store, retrieve, and learn from past experiences to improve their decision-making performance over time.

What is memory distillation in this context?

Memory distillation is the process of consolidating multiple similar experiences into high-level patterns, which helps prune redundant data and improves the quality of agent retrieval.

How much faster is AgentDB compared to legacy systems?

AgentDB provides a significant performance boost, with pattern retrieval being up to 150x faster and batch operations up to 500x faster than legacy ReasoningBank implementations.

Is this skill backward compatible?

Yes, it maintains 100% backward compatibility with legacy ReasoningBank APIs while automatically upgrading the backend to the faster AgentDB engine.

ReasoningBank Agent Learning

Name: ReasoningBank Agent Learning
Author: adebold

byadebold

0•

Ciencia de Datos y ML

Implements adaptive learning and high-speed memory patterns for self-improving Claude Code agents using AgentDB.

ReasoningBank with AgentDB provides a robust framework for building intelligent agents that learn from experience. By utilizing AgentDB’s high-performance vector database, this skill enables features like trajectory tracking, verdict judgment, and memory distillation at speeds up to 150x faster than traditional methods. It is ideal for developers building autonomous agents that need to refine their decision-making processes over time, optimize task execution paths, and maintain high-confidence knowledge bases through automatic pattern recognition and experience replay.

Características Principales

01High-performance vector memory with sub-millisecond access times

02Verdict judgment system to evaluate and improve decision outcomes

03Trajectory tracking to record and analyze agent execution paths

04Context synthesis for generating rich narrative insights from memories

05Automated memory distillation to consolidate experiences into patterns

060 GitHub stars

Casos de Uso

01Building self-improving agents that learn from past successes and failures

02Implementing experience replay systems for reinforcement learning agents

03Optimizing complex decision-making workflows in autonomous coding tasks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add adebold/warehouse-network reasoningbank-agentdb

For use in Claude.ai and ChatGPT

Download Skill