executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
Explorer les Skills
Productivité · SKILL.md
smart-routing
smart-routingComplexity-based task routing with Q-Learning optimization, Agent Booster WASM fast-path, and Mixture-of-Experts model selection.
Independent GitHub snapshot · Automated classification · Original documentation governs
Documentation de la Skill
GitHubname: 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] skillAreas: [skill-area:agentic-loops, skill-area:orchestration-loop] workflows: [workflow:feature-development] topics: [topic:developer-experience] roles: [role:tech-lead, role:backend-engineer]
- 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