smart-routing
SkillProductivityLets your agent pick the best model and route each task automatically based on how complex it is.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the smart-routing skill
About this capability
Complexity-based task routing with Q-Learning optimization, Agent Booster WASM fast-path, and Mixture-of-Experts model selection.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/methodologies/ruflo/skills/smart-routing/SKILL.md and read by ahel’s review.
- 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 modernizationadd-types- TypeScript type annotation insertionadd-error-handling- Try/catch wrapper insertionasync-await- Promise chain to async/await conversionextract-function- Code block extraction to named functionsadd-jsdoc- Documentation generation
Agents Used
agents/optimizer/- Performance and cost optimizationagents/architect/- Complex task decomposition
Tool Use
Invoke via babysitter process: methodologies/ruflo/ruflo-task-routing
Signals
- GitHub stars
- 2k
- Forks
- 106
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
smart-routing- Source
- github.com/a5c-ai/babysitter