Agentic-creator-os model-routing
Intelligent model selection - routes tasks to Haiku (fast/cheap), Sonnet (balanced), or Opus (complex/strategic) based on task complexity analysis
install
source · Clone the upstream repo
git clone https://github.com/frankxai/agentic-creator-os
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/frankxai/agentic-creator-os "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/model-routing" ~/.claude/skills/frankxai-agentic-creator-os-model-routing && rm -rf "$T"
manifest:
.claude/skills/model-routing/SKILL.mdsource content
Model Routing System
You have access to intelligent model routing. Before executing any task, analyze complexity and route to the appropriate model tier.
Routing Decision Matrix
TASK COMPLEXITY ANALYSIS ──────────────────────────────────────────────────────────────── HAIKU (Fast, Cheap) - Use for: ├── Simple file operations (read, list, navigate) ├── Scaffolding and boilerplate generation ├── Deterministic transformations (format, lint, compile) ├── Status checks and health monitoring ├── SEO metadata generation ├── Deployment commands (after code is written) ├── Documentation formatting ├── Simple search and replace │ │ Token cost: ~$0.25/1M input, $1.25/1M output │ Latency: Fastest │ Use when: Task has clear, unambiguous steps SONNET (Balanced) - Use for: ├── Feature implementation (standard complexity) ├── Bug fixes requiring analysis ├── Content writing (articles, social posts) ├── Code review and quality checks ├── Test generation ├── Refactoring with clear patterns ├── API integration work ├── Database schema design │ │ Token cost: ~$3/1M input, $15/1M output │ Latency: Medium │ Use when: Task requires reasoning but not deep strategy OPUS (Strategic, Complex) - Use for: ├── Architecture decisions (system design) ├── Multi-agent coordination (council, swarm) ├── Strategic planning (business, product) ├── Complex debugging (multi-file, subtle bugs) ├── Security audits and vulnerability analysis ├── Enterprise AI system design ├── Book writing (narrative, character development) ├── Research synthesis (multiple sources) ├── Ambiguous requirements interpretation │ │ Token cost: ~$15/1M input, $75/1M output │ Latency: Slowest but most capable │ Use when: Task requires deep reasoning, creativity, or strategy
Automatic Routing Rules
When processing a request, apply these rules:
Route to HAIKU when:
- User says: "deploy", "format", "lint", "check status", "list", "scaffold"
- File patterns:
,*.config.*
,package.jsontsconfig.json - Commands:
,/mcp-status
,/inventory-status
(execution phase)/nextjs-deploy
Route to SONNET when:
- User says: "write", "implement", "fix", "create", "build", "test"
- File patterns:
,*.ts
,*.tsx
,*.py
(content files)*.md - Commands:
,/article-creator
,/create-music
,/spec/generate-social
Route to OPUS when:
- User says: "design", "architect", "strategy", "council", "analyze", "research"
- Keywords: "enterprise", "system", "multi-agent", "complex", "strategic"
- Commands:
,/starlight-architect
,/council
,/author-team/research
Cost Optimization
BEFORE (No routing): All tasks → Opus → $75/1M output tokens AFTER (With routing): Simple tasks (40%) → Haiku → $1.25/1M = $0.50 Medium tasks (45%) → Sonnet → $15/1M = $6.75 Complex tasks (15%) → Opus → $75/1M = $11.25 ────────────────────────────────────────────── TOTAL: $18.50 vs $75 = 75% cost reduction
Implementation in Task Tool
When using the Task tool, specify model based on routing:
// Simple task - use haiku Task({ subagent_type: "Explore", model: "haiku", prompt: "List all files in src/" }) // Medium task - use sonnet (default) Task({ subagent_type: "code-reviewer", model: "sonnet", prompt: "Review this PR for issues" }) // Complex task - use opus Task({ subagent_type: "Plan", model: "opus", prompt: "Design the architecture for a multi-tenant SaaS platform" })
Command-Level Routing
| Command | Default Model | Rationale |
|---|---|---|
| sonnet | Router needs reasoning |
| sonnet | Content creation |
| sonnet | Creative work |
| sonnet | Research + creation |
| opus | Strategic design |
| opus | Multi-perspective |
| sonnet | Information synthesis |
| sonnet | Feature planning |
| haiku | Execution |
| haiku | Status check |
| haiku | Status check |
| haiku | Execution |
| sonnet | Editing |
| sonnet | Quality check |
Escalation Pattern
If a haiku-routed task fails or produces poor results:
- Automatically escalate to sonnet
- If still failing, escalate to opus
- Log escalation for learning
haiku (attempt) → fail → sonnet (retry) → fail → opus (final)
Model Routing v1.0 - Implementing claude-flow's intelligent routing pattern