smart-routing

name	smart-routing
description	Complexity-based task routing with Q-Learning optimization, Agent Booster WASM fast-path, and Mixture-of-Experts model selection.
allowed-tools	Read, Write, Edit, Bash, Grep, Glob, WebFetch, WebSearch, Agent, AskUserQuestion

Smart Routing

Overview

Intelligent task routing using Q-Learning to select optimal execution paths. Simple tasks route to Agent Booster (WASM, <1ms, $0), medium tasks to efficient models, and complex tasks to Opus + multi-agent swarms.

When to Use

• Optimizing cost vs. quality tradeoffs for diverse task types
• When tasks range from simple transforms to complex multi-file changes
• Reducing latency for common code transformations
• Learning from routing history to improve future decisions

Routing Tiers

Tier	Target	Latency	Cost
Agent Booster	Simple transforms (var-to-const, add-types)	<1ms	$0
Medium	Standard coding tasks	~500ms	Low
Complex	Multi-agent swarm coordination	2-5s	Higher

Agent Booster Transforms

• var-to-const - Variable declaration modernization
• add-types - TypeScript type annotation insertion
• add-error-handling - Try/catch wrapper insertion
• async-await - Promise chain to async/await conversion
• extract-function - Code block extraction to named functions
• add-jsdoc - Documentation generation

Agents Used

• agents/optimizer/ - Performance and cost optimization
• agents/architect/ - Complex task decomposition

Tool Use

Invoke via babysitter process: methodologies/ruflo/ruflo-task-routing