How does this skill prevent AI intelligence failures?

By improving retrieval accuracy, it prevents agents from 'forgetting' key facts or providing contradictory answers, which are often retrieval issues rather than storage problems.

What is the primary focus of the Agent Memory Systems skill?

It focuses on the architecture of agent memory, prioritizing effective retrieval strategies like chunking and embedding over simple data storage to ensure AI agents remain consistent.

Does this skill handle memory decay?

Yes, it includes capabilities for managing memory formation and decay, as well as temporal scoring to ensure the most relevant information is prioritized.

Does it provide guidance on specific database types?

Yes, it includes patterns for vector store selection and helps developers choose the right database for their specific agentic use case.

Agent Memory Systems

Name: Agent Memory Systems
Author: claudiodearaujo

byclaudiodearaujo

Ciencia de Datos y ML

Implements sophisticated cognitive architectures for AI agents to manage short-term, long-term, and episodic memory effectively.

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This skill transforms Claude into a cognitive architect capable of designing robust memory systems for AI agents. It focuses on the critical distinction between storage and retrieval, providing expert guidance on vector store selection, optimal chunking strategies, and embedding quality. By managing the full lifecycle of agent data—from memory formation and decay to semantic and procedural categorization—this skill prevents intelligence failures caused by inconsistent or forgotten information in complex, multi-interaction environments.

Características Principales

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Vector database selection and implementation patterns for diverse use cases
Contextual chunking based on Anthropic's latest architectural approaches
Strategic chunking and embedding optimization for high-precision retrieval
Conflict detection and temporal scoring to maintain memory consistency
Advanced memory architecture design (Short-term, Long-term, Working)

Casos de Uso

Optimizing RAG (Retrieval-Augmented Generation) pipelines for improved accuracy
Developing multi-agent systems that need to share and sync complex knowledge bases
Building long-running autonomous agents that require persistent context across sessions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claudiodearaujo/sistema-de-narra-o-de-livro-front agent-memory-systems

For use in Claude.ai and ChatGPT

Download Skill

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