How does AgentDB improve Claude's memory performance?

AgentDB uses HNSW indexing and advanced quantization techniques (binary/scalar) to provide search results between 150x and 12,500x faster than traditional memory solutions.

What types of learning algorithms are supported?

The skill includes 9 learning templates, including Decision Transformer, Q-Learning, Actor-Critic, SARSA, and Curiosity-Driven learning algorithms.

Can I migrate my existing data to this skill?

Yes, it includes built-in migration tools specifically designed to transition legacy ReasoningBank data into the optimized AgentDB format.

Is memory storage efficient for large datasets?

Yes, AgentDB supports scalar and binary quantization, which can reduce memory usage by 4x to 32x while maintaining high retrieval accuracy.

How do I connect this skill to Claude Code?

You can use the 'npx agentdb@latest mcp' command to launch the Model Context Protocol server and link it directly to your Claude Code instance.

AgentDB Memory Patterns

Name: AgentDB Memory Patterns
Author: ellisapotheosis

byellisapotheosis

데이터 과학 및 ML

Implements high-performance persistent memory and learning patterns for stateful AI agents using AgentDB.

소개

This skill equips AI agents with advanced memory management capabilities, allowing them to maintain context across sessions and learn from historical interactions. By leveraging AgentDB's persistent storage and ReasoningBank integration, it provides structured patterns for session memory, long-term fact storage, and pattern recognition. It is particularly useful for developers building complex assistants or autonomous agents within Claude Code that require high-speed vector search, hierarchical memory organization, and reinforcement learning-based optimization to improve performance over time.

주요 기능

Pattern learning with 9 built-in reinforcement learning algorithms
Persistent session and long-term memory management
0 GitHub stars
Memory consolidation and hierarchical organization strategies
High-performance vector search with HNSW indexing and caching
Native MCP server integration for seamless Claude Code connectivity

사용 사례

Developing autonomous agents that optimize behavior through interaction patterns
Implementing context-aware coding assistants for large-scale software projects
Building stateful chat systems that retain user preferences and history

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ellisapotheosis/project-nyra agentdb-memory-patterns

For use in Claude.ai and ChatGPT

Download Skill

GitHub

소개