smart-routing

# 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`