eliza

Create personality-driven AI agents with plugins, memory, and multi-platform connectors.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/labsaistudio/AABC-Labs --skill eliza-labsaistudio
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: eliza
Source: https://github.com/labsaistudio/AABC-Labs/tree/main/backend/agent/skills/catalog/eliza
Command: npx skills add https://github.com/labsaistudio/AABC-Labs --skill eliza-labsaistudio

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

ElizaOS enables developers to create, deploy, and manage autonomous AI agents with persistent personalities, multi-platform presence, and on-chain capabilities, reducing the complexity of building multi-agent systems.

Core Features & Use Cases

  • Character-file driven agents: define identities, memory, and behavior; - Plugin system for extensibility; - Platform connectors for Discord, Telegram, Twitter, Farcaster; - RAG-based memory and knowledge management; - Solana wallet integration for on-chain tasks. Use cases include research assistants, automation agents, and on-chain operation orchestrators.

Quick Start

Install the ElizaOS CLI and run elizaos start with a sample character to launch a multi-agent system.

Frequently Asked Questions about eliza

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build autonomous AI agents with persistent personalities across multiple platforms?

To build autonomous AI agents with persistent personalities, use a character-file driven framework that defines identities, manages memory through RAG, and connects to platforms like Discord, Telegram, Twitter, and Farcaster. This approach reduces the complexity of multi-agent systems.

Can I use ElizaOS to deploy on-chain task bots for Solana?

Yes, you can deploy on-chain task bots for Solana using this framework. It includes Solana wallet integration, allowing autonomous AI agents to execute on-chain operations and orchestrate tasks natively alongside their standard automation capabilities.

What is the best way to create a multi-agent system with RAG-based memory?

The best way to create a multi-agent system with RAG-based memory is using a framework that combines character files for behavior definition with persistent knowledge management. This setup enables agents to maintain context and recall information accurately.

Does this framework support custom interfaces and platform connectors for automation agents?

Yes, the framework supports custom interfaces alongside built-in platform connectors for Discord, Telegram, Twitter, and Farcaster. This allows automation agents and research assistants to operate seamlessly across multiple communication channels.

How do I start building AI agents with the ElizaOS CLI?

To start building AI agents with the ElizaOS CLI, install the CLI tool and run the start command with a sample character file. This quickly launches a multi-agent system, which you can then extend using plugins and custom configurations.

What are the limitations of character-file driven AI agents for multi-platform deployment?

Character-file driven AI agents require a root SKILL.md with specific YAML frontmatter defining name, description, license, and category. While highly extensible through optional directories, complex multi-platform deployments may require additional custom plugin development.