smart-routing ยท diff
git:20260325.a6b3a88 to git:20260507.56f011d
47 added, 44 removed. Audit A to A.
- ---
- 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`
+ ---
+ 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
+ graph:
+ domains: [domain:software-engineering]
+
+ ---
+
+ # 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`