What is ReasoningBank with AgentDB?

It is a specialized skill for Claude Code that enables self-learning capabilities for AI agents by using a high-performance vector database to store and retrieve past experiences.

Does this skill require modifying existing ReasoningBank code?

No, it is designed with 100% backward compatibility, allowing you to use existing ReasoningBank APIs while benefiting from the AgentDB backend automatically.

What is memory distillation in this context?

Memory distillation is the process of consolidating multiple similar experiences into a single, high-level pattern, which helps in reducing noise and improving decision-making accuracy.

How much faster is AgentDB than legacy solutions?

AgentDB provides up to 150x faster pattern retrieval and 500x faster batch operations, significantly reducing latency in agentic reasoning tasks.

ReasoningBank with AgentDB

Name: ReasoningBank with AgentDB
Author: ricable

byricable

•

Data Science & ML

Implements high-performance adaptive learning and memory distillation for AI agents using the AgentDB vector engine.

This skill integrates ReasoningBank adaptive learning patterns with AgentDB's high-performance backend to enable Claude to build self-improving agents. It provides a robust framework for trajectory tracking, outcome judgment, and memory distillation, allowing agents to learn from past experiences and optimize decision-making processes. With performance improvements of up to 150x for pattern retrieval and full backward compatibility, it is ideal for developers implementing reinforcement learning concepts or complex experience replay systems in AI agent workflows.

Key Features

01Experience trajectory tracking and outcome judgment for agents

022 GitHub stars

03High-speed vector database integration (150x-12,500x faster performance)

04Advanced reasoning modules including PatternMatcher and ContextSynthesizer

05100% backward compatibility with legacy ReasoningBank APIs

06Automated memory distillation and pattern consolidation

Use Cases

01Building self-learning AI agents that improve based on past successes and failures

02Optimizing complex decision-making workflows through experience replay systems

03Implementing persistent, searchable long-term memory for autonomous agent clusters

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ricable/ultimate-ai-agent reasoningbank-agentdb

For use in Claude.ai and ChatGPT

Download Skill