Can I use this skill for multi-agent systems?

Yes, it includes specialized documentation and patterns for handling messages and coordination between multiple Letta agents.

What is the Letta framework?

Letta is an open-source framework designed for building stateful AI agents that utilize long-term memory and tool integration to perform complex tasks.

How does this skill help with Letta development?

It provides instant access to API references, code snippets for the Letta SDK, and best practices for managing agent memory and tool configurations.

Does this skill include deployment information?

Yes, the skill contains reference materials on deployment strategies to help you move your Letta agents from local development to production environments.

Letta AI Agent Framework

Name: Letta AI Agent Framework
Author: delorenj

bydelorenj

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Data Science & ML

Simplifies building and managing stateful AI agents with long-term memory using the Letta framework.

About

The Letta skill provides comprehensive assistance for developing sophisticated AI agents that maintain state and long-term memory. It offers deep integration with Letta's API and SDK, guiding developers through agent creation, memory management, tool integration, and multi-agent system orchestration. By leveraging official documentation and common implementation patterns, this skill helps streamline the entire development lifecycle—from initial setup and local deployment to debugging complex agent interactions and persistent data blocks.

Key Features

Comprehensive API and SDK reference for Python development
Seamless tool integration and custom tool development guides
Deployment guidance for production-ready AI agent architectures
5 GitHub stars
Stateful agent construction with persistent long-term memory
Multi-agent system orchestration and message management

Use Cases

Orchestrating multi-agent workflows where agents share memory and collaborate on tasks
Building a personal assistant bot that remembers user history across sessions
Developing specialized research agents that use custom tools to query external data

About

Key Features

Comprehensive API and SDK reference for Python development
Seamless tool integration and custom tool development guides
Deployment guidance for production-ready AI agent architectures
5 GitHub stars
Stateful agent construction with persistent long-term memory
Multi-agent system orchestration and message management

Use Cases

Orchestrating multi-agent workflows where agents share memory and collaborate on tasks
Building a personal assistant bot that remembers user history across sessions
Developing specialized research agents that use custom tools to query external data