msia-agent

Name: msia-agent
Availability: InStock
Author: Pepe

Route customer-support intents and orchestrate tools in LangGraph agent workflows.

Updated Jan 7, 2026

Search Tags:#agent #langgraph #state-management #customer-support #intent-routing #mode-based

Ready to run

npx skills add https://github.com/pepeccz/msi-a --skill msia-agent

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: msia-agent
Source: https://github.com/pepeccz/msi-a/tree/main/skills/msia-agent
Command: npx skills add https://github.com/pepeccz/msi-a --skill msia-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

MSI-a pattern for building scalable LangGraph-based conversational agents to route intents, manage state, and orchestrate tools in customer-support flows.

Core Features & Use Cases

Mode-based architecture with CONSULTA, PRESUPUESTO, EXPEDIENTE, EVALUACION_GATEWAY, and ESCALATION workflows.
Tool-driven state management and per-mode retry policies to ensure reliability.
Reusable prompt loading and per-mode context assembly for cost-efficient LLM usage.
Use Case: Automate pricing, data collection, and customer inquiries in automotive homologation workflows.

Quick Start

Instantiate a LangGraph-based agent pattern for customer support with mode-based routing and tool orchestration.

Frequently Asked Questions about msia-agent

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

FAQPage Schema

How do I build a LangGraph agent for customer support with mode-based routing?▼

Build a LangGraph customer support agent by classifying user intent and routing queries to specific modes like CONSULTA or EXPEDIENTE. This pattern orchestrates tools for chatbot workflows, handling prompt assembly and state persistence automatically.

What is intent routing in LangGraph state-management for chatbots?▼

Intent routing in LangGraph state-management directs user queries to designated agent modes. It evaluates intent classification to switch between workflows like PRESUPUESTO or EVALUATION_GATEWAY, ensuring chatbots execute the correct tool-driven state contracts.

How do I manage state persistence across different agent modes in LangGraph?▼

Manage state persistence across agent modes by applying a tool-driven state-management contract. The agent enforces per-mode retry logic and reusable prompt loading, ensuring reliable state tracking during mode switching for EXPEDIENTE and PRESUPUESTO workflows.

Does this agent pattern support automotive homologation workflows?▼

Yes, the agent pattern supports automotive homologation workflows by automating pricing, data collection, and customer inquiries. It uses mode-based architecture to handle specific processes like EXPEDIENTE and PRESUPUESTO within the automotive domain.

How do I handle retry logic for failed tool calls in a LangGraph agent?▼

Handle failed tool calls in a LangGraph agent by implementing per-mode retry policies. The architecture defines retry logic within each specific agent mode, ensuring reliable tool orchestration and state management during customer support interactions.

What is the best way to assemble prompts dynamically for different chatbot modes?▼

Assemble prompts dynamically by using reusable prompt loading combined with per-mode context assembly. This approach constructs specific prompts based on the active agent mode, optimizing LLM usage and managing costs efficiently.