libagent - Agent orchestration library for conversational AI. AgentMind class coordinates LLM completions, memory management, tool execution, and multi-turn conversations. AgentAction handles tool calls and action processing. Use for building chat agents, RAG pipelines, and AI assistants. Integrates with libmemory, librpc, and libllm
Scanned 2/12/2026
Install to Claude Code
npx -y skills add majiayu000/claude-skill-registry --skill libagent --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: libagent
description: >
libagent - Agent orchestration library for conversational AI. AgentMind class
coordinates LLM completions, memory management, tool execution, and multi-turn
conversations. AgentAction handles tool calls and action processing. Use for
building chat agents, RAG pipelines, and AI assistants. Integrates with
libmemory, librpc, and libllm
---
# libagent Skill
## When to Use
- Building conversational AI agents with tool capabilities
- Coordinating LLM completions with memory context
- Processing multi-turn conversations with state
- Implementing RAG (retrieval-augmented generation) pipelines
## Key Concepts
**AgentMind**: Core reasoning engine that processes requests through LLM
completions, manages conversation state, and coordinates tool execution.
**AgentAction**: Handles individual tool calls, executes actions, and returns
results to the conversation flow.
## Usage Patterns
### Pattern 1: Basic agent request
```javascript
import { AgentMind } from "@copilot-ld/libagent";
const mind = new AgentMind(memoryClient, llmClient, toolClient);
const response = await mind.process({
resourceId: conversationId,
content: "What is the weather?",
});
```
### Pattern 2: Streaming responses
```javascript
for await (const chunk of mind.stream(request)) {
process.stdout.write(chunk.content);
}
```
## Integration
Works with `libmemory` for context windows, `librpc` for gRPC clients, and
`libllm` for completions. Used by the Agent service.
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