AI Infrastructure

Model Router Skill

Production LLM routing that routes tasks to the right provider, recovers automatically when APIs fail, and optimizes for cost without sacrificing quality.

Version 4.4 · Active in Production 5+ Providers

The Problem

LLM providers fail. Rate limits hit. Models get deprecated. Most agent systems hard-code a single provider and crash when it goes down. Or they waste money routing simple tasks to expensive models when a cheaper one would do the job just as well.

You need a system that routes intelligently, fails gracefully, and gets better over time.

Architecture

The Model Router evaluates every task against provider capabilities, current health, and cost constraints. It selects the optimal provider, executes with automatic fallback, and monitors performance for future optimization. 

Task Request
    │
    ▼
Capability Analysis
    │
    ├────────┐
    │              │
Provider Health  Cost Check
    │              │
    └────────┘
    │
    ▼
Provider Selection
    │
    ▼
Execution with Fallback
    │
    ▼
Performance Logging

What This Demonstrates

  • Production resilience — Provider abstraction and automatic failover keep agents running when APIs go down.
  • Cost optimization — Matching task complexity to model capability saves money without sacrificing quality.
  • Real-world evaluation — Active in an agent system (Hermes) where routing decisions affect every task.
  • Iterative improvement — v4.4 evolved from production usage patterns, not theoretical design.