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.md
source 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.json
    ,
    tsconfig.json
  • Commands:
    /mcp-status
    ,
    /inventory-status
    ,
    /nextjs-deploy
    (execution phase)

Route to SONNET when:

  • User says: "write", "implement", "fix", "create", "build", "test"
  • File patterns:
    *.ts
    ,
    *.tsx
    ,
    *.py
    ,
    *.md
    (content files)
  • 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

CommandDefault ModelRationale
/acos
sonnetRouter needs reasoning
/article-creator
sonnetContent creation
/create-music
sonnetCreative work
/infogenius
sonnetResearch + creation
/starlight-architect
opusStrategic design
/council
opusMulti-perspective
/research
sonnetInformation synthesis
/spec
sonnetFeature planning
/nextjs-deploy
haikuExecution
/mcp-status
haikuStatus check
/inventory-status
haikuStatus check
/publish
haikuExecution
/polish-content
sonnetEditing
/review-content
sonnetQuality check

Escalation Pattern

If a haiku-routed task fails or produces poor results:

  1. Automatically escalate to sonnet
  2. If still failing, escalate to opus
  3. Log escalation for learning
haiku (attempt) → fail → sonnet (retry) → fail → opus (final)

Model Routing v1.0 - Implementing claude-flow's intelligent routing pattern