Can I migrate my existing data to this skill?

Yes, the skill provides a migration utility to automatically transfer patterns and data from legacy ReasoningBank databases into the optimized AgentDB format.

What learning algorithms are supported?

The skill supports 9 algorithms, including Decision Transformers, Q-Learning, SARSA, Actor-Critic, Active Learning, and Curiosity-driven learning.

How fast is AgentDB compared to traditional solutions?

AgentDB is significantly faster than standard solutions, offering up to 150x speed improvements for pattern searches and up to 12,500x speed for large-scale queries.

Does this skill work with Claude Code via MCP?

Yes, it includes a dedicated MCP (Model Context Protocol) server integration that allows Claude Code to directly interact with and manage AgentDB memory stores.

What is AgentDB Memory Patterns?

It is a specialized skill for Claude Code that enables persistent, long-term memory for AI agents using the AgentDB vector database and ReasoningBank framework.

AgentDB Memory Patterns

Name: AgentDB Memory Patterns
Author: nbossn

bynbossn

0•

データサイエンスとML

Implements high-performance persistent memory and reinforcement learning patterns for AI agents and intelligent assistants.

AgentDB Memory Patterns provides a robust framework for managing AI agent state, session history, and long-term knowledge using a high-performance vector database. By integrating with ReasoningBank, it allows agents to learn from interactions using advanced algorithms like Decision Transformers and Q-Learning while maintaining 100% backward compatibility. This skill is essential for developers building sophisticated, stateful AI systems that require context-aware reasoning and lightning-fast retrieval speeds—up to 12,500x faster than traditional storage solutions.

主な機能

010 GitHub stars

02High-performance vector search with HNSW indexing and quantization

03Persistent session and long-term memory management

04Context synthesis and automated memory consolidation for optimized retrieval

059 built-in reinforcement learning algorithms including Decision Transformer and Actor-Critic

06Seamless MCP server integration for direct use within Claude Code

ユースケース

01Optimizing large-scale retrieval-augmented generation (RAG) workflows with high-speed indexing

02Implementing learning-based agents that improve decision-making via reinforcement learning

03Building stateful AI chat systems that remember user preferences across sessions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nbossn/claude-code-base agentdb-memory-patterns

For use in Claude.ai and ChatGPT

主な機能

010 GitHub stars

02High-performance vector search with HNSW indexing and quantization

03Persistent session and long-term memory management

04Context synthesis and automated memory consolidation for optimized retrieval

059 built-in reinforcement learning algorithms including Decision Transformer and Actor-Critic

06Seamless MCP server integration for direct use within Claude Code

ユースケース

01Optimizing large-scale retrieval-augmented generation (RAG) workflows with high-speed indexing

02Implementing learning-based agents that improve decision-making via reinforcement learning

03Building stateful AI chat systems that remember user preferences across sessions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nbossn/claude-code-base agentdb-memory-patterns

For use in Claude.ai and ChatGPT