Awesome-Memory-for-Agents

🥈Silver

A curated list of papers on memory for language agents. Helps operations teams build agents with improved recall and context retention. Integrates with Claude to enhance agent performance in customer service and data analysis workflows.

295140Updated 1w ago

Intermediate30min to implementautomation

Saves ~25 min per use

Quick InstallView Source

git clone https://github.com/TsinghuaC3I/Awesome-Memory-for-Agents.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/TsinghuaC3I/Awesome-Memory-for-Agents

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Generate a summary of the key findings from recent research papers on memory mechanisms for language agents. Focus on papers published in the last 2 years. Include insights on how these mechanisms can be applied to improve the performance of AI agents in [INDUSTRY] for [COMPANY].

Example Output

# Summary of Recent Research on Memory Mechanisms for Language Agents

## Key Findings
- **Memory Augmentation**: Recent studies highlight the importance of memory augmentation in enhancing the contextual understanding of language agents. Techniques such as external memory modules and episodic memory have shown significant improvements in task performance.
- **Attention Mechanisms**: The use of attention mechanisms in memory retrieval has been found to improve the accuracy and efficiency of language agents. This is particularly useful in scenarios requiring quick decision-making.
- **Long-Term Memory**: Research indicates that integrating long-term memory can help language agents maintain consistency and coherence over extended interactions. This is crucial for applications in customer service and personal assistants.
- **Adaptive Learning**: Adaptive learning techniques allow language agents to update their memory dynamically, making them more versatile and capable of handling a wide range of tasks.

## Applications in [INDUSTRY]
- **Customer Service**: Implementing these memory mechanisms can enhance the ability of AI agents to provide personalized and context-aware responses, improving customer satisfaction.
- **Personal Assistants**: Language agents with advanced memory capabilities can better manage schedules, reminders, and other tasks, making them more reliable and efficient.
- **Automation**: In industrial settings, memory-augmented language agents can streamline processes by retaining and applying knowledge from previous interactions, reducing the need for human intervention.