nexagent

Orchestrate LLMs, tools, and channels with YAML-driven phase workflows.

1|Updated Dec 29, 2025
One-click install
npx skills add https://github.com/nextlw/nexagent --skill nexagent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nexagent
Source: https://github.com/nextlw/nexagent/tree/main/skill_extracted/nexagent
Command: npx skills add https://github.com/nextlw/nexagent --skill nexagent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

NexAgent provides a modular framework to build intelligent agents that orchestrate LLMs, tools, and channels, reducing boilerplate and enabling scalable decision-making.

Core Features & Use Cases

  • Declarative Tools and Phases for complex workflows (tools, phases.yaml, channels)
  • Multi-Channel support (WhatsApp, Telegram, HTTP API) and observability
  • Production-grade resilience with circuit breakers, caching, hot reload and multi-tenant capabilities
  • Use Case: Build an enterprise-grade support agent that handles inquiries, checks inventory via tools, schedules appointments, and replies with channel-appropriate outputs.

Quick Start

Create a NexAgent project skeleton and begin implementing tools, phases, and channels to deploy a production-grade AI agent.

Frequently Asked Questions about nexagent

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

FAQPage Schema
How do I build production-grade AI agents that orchestrate LLMs, tools, and channels?▼

You can build production-grade AI agents by using a modular framework that orchestrates LLMs, tools, and channels through declarative YAML-driven phase workflows, reducing boilerplate for scalable decision-making.

How do I define complex workflows for autonomous AI agents?▼

You define complex agent workflows declaratively using YAML-driven phases, configuring tools and multi-channel outputs to orchestrate sequential logic and scalable decision-making without heavy boilerplate.

Can I deploy autonomous AI agents to WhatsApp and Telegram?▼

Yes, you can deploy autonomous AI agents across multiple channels including WhatsApp, Telegram, and HTTP APIs, enabling channel-appropriate outputs and comprehensive observability for production environments.

Do I need circuit breakers and caching for multi-tenant AI agent deployments?▼

Circuit breakers and caching are optional for multi-tenant AI agent deployments, but they provide production-grade resilience by preventing cascading failures and optimizing tool execution performance.

What is the best way to add custom tools to an LLM agent framework?▼

The best way to add custom tools is through a modular tool registry, implementing tools with optional caching and circuit breakers, and using references and assets for extensibility.

Does NexAgent support Railway and Docker for deploying agent workflows?▼

Yes, NexAgent supports Railway and Docker deployment tools, allowing you to containerize and deploy production-grade AI agent workflows with hot reload and multi-tenant capabilities.