libagent

Name: libagent
Availability: InStock
Author: Copilot-LD

Orchestrate LLM completions, memory windows, and tool calls for conversational AI workflows.

1|1|Updated Aug 7, 2025

Search Tags:#llm #rag #agent #memory #conversational-ai #tool-calls

Ready to run

npx skills add https://github.com/copilot-ld/copilot-ld --skill libagent

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: libagent
Source: https://github.com/copilot-ld/copilot-ld/tree/main/packages/libagent
Command: npx skills add https://github.com/copilot-ld/copilot-ld --skill libagent

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

libagent provides a modular library to orchestrate LLM-based agents by coordinating memory, completions, and tool execution to enable robust, multi-turn conversations and retrieval workflows.

Core Features & Use Cases

Orchestrates AgentMind, AgentHands, and integrations with memory, LLM, and tool services to build chat agents and RAG pipelines.
Supports multi-turn conversations, memory windows, parallel tool calls, and streaming responses.

Quick Start

Instantiate an AgentMind with memory, llm, and tool clients and run process on a sample interaction.

Frequently Asked Questions about libagent

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

FAQPage Schema

How do I build a multi-turn conversational AI agent with memory and tool calls?▼

To build a multi-turn conversational AI agent, you orchestrate LLM completions, memory windows, and parallel tool calls using a modular library that coordinates memory management, resource indexing, and tool execution for robust chat interactions.

What is the best way to orchestrate retrieval-augmented generation pipelines with LLMs?▼

The best way to orchestrate retrieval-augmented generation pipelines is by coordinating LLM completions and memory windows with tool execution, enabling an end-to-end agent workflow across knowledge bases with streaming responses.

How does parallel tool execution work in AI agent workflows?▼

Parallel tool execution in AI agent workflows works by coordinating AgentHands with memory and LLM services, allowing multiple tool calls to process simultaneously during multi-turn conversations and retrieval workflows.

Can I use my existing memory and LLM clients to create a chat agent?▼

Yes, you can instantiate an AgentMind with your existing memory, LLM, and tool clients, integrating with libmemory, librpc, and libllm to run process on sample interactions for end-to-end agent workflows.

Does this agent orchestration library support streaming responses and optional handoffs?▼

Yes, this agent orchestration library supports streaming responses and optional handoffs, coordinating LLM completions, memory windows, and tool calls to enable robust conversational AI workflows.