model-router
A comprehensive AI model routing system that automatically selects the optimal model.
Installation
npx clawhub@latest install model-routerView the full skill documentation and source below.
Documentation
Model Router
Intelligent AI model routing across multiple providers for optimal cost-performance balance.
Automatically select the best model for any task based on complexity, type, and your preferences. Support for 6 major AI providers with secure API key management and interactive configuration.
π― What It Does
- Analyzes tasks and classifies them by type (coding, research, creative, simple, etc.)
- Routes to optimal models from your configured providers
- Optimizes costs by using cheaper models for simple tasks
- Secures API keys with file permissions (600) and isolated storage
- Provides recommendations with confidence scoring and reasoning
π Quick Start
Step 1: Run the Setup Wizard
cd skills/model-router
python3 scripts/setup-wizard.py
The wizard will guide you through:
Step 2: Use the Classifier
# Get model recommendation for a task
python3 scripts/classify_task.py "Build a React authentication system"
# Output:
# Recommended Model: claude-sonnet
# Confidence: 85%
# Cost Level: medium
# Reasoning: Matched 2 keywords: build, system
Step 3: Route Tasks with Sessions
# Spawn with recommended model
sessions_spawn --task "Debug this memory leak" --model claude-sonnet
# Use aliases for quick access
sessions_spawn --task "What's the weather?" --model haiku
π Supported Providers
| Provider | Models | Best For | Key Format |
| Anthropic | claude-opus-4-5, claude-sonnet-4-5, claude-haiku-4-5 | Coding, reasoning, creative | sk-ant-... |
| OpenAI | gpt-4o, gpt-4o-mini, o1-mini, o1-preview | Tools, deep reasoning | sk-proj-... |
| Gemini | gemini-2.0-flash, gemini-1.5-pro, gemini-1.5-flash | Multimodal, huge context (2M) | AIza... |
| Moonshot | moonshot-v1-8k/32k/128k | Chinese language | sk-... |
| Z.ai | glm-4.5-air, glm-4.7 | Cheapest, fast | Various |
| GLM | glm-4-flash, glm-4-plus, glm-4-0520 | Chinese, coding | ID.secret |
ποΈ Task Type Mappings
Default routing (customizable via wizard):
| Task Type | Default Model | Why |
simple | glm-4.5-air | Fastest, cheapest for quick queries |
coding | claude-sonnet-4-5 | Excellent code understanding |
research | claude-sonnet-4-5 | Balanced depth and speed |
creative | claude-opus-4-5 | Maximum creativity |
math | o1-mini | Specialized reasoning |
vision | gemini-1.5-flash | Fast multimodal |
chinese | glm-4.7 | Optimized for Chinese |
long_context | gemini-1.5-pro | Up to 2M tokens |
π° Cost Optimization
Aggressive Mode
Always uses the cheapest capable model:- Simple β glm-4.5-air (~10% cost)
- Coding β claude-haiku-4-5 (~25% cost)
- Research β claude-sonnet-4-5 (~50% cost)
Balanced Mode (Default)
Considers cost vs quality:- Simple tasks β Cheap models
- Critical tasks β Premium models
- Automatic escalation if cheap model fails
Quality Mode
Always uses the best model regardless of costπ Security
API Key Storage
~/.model-router/
βββ config.json # Model mappings (chmod 600)
βββ .api-keys # API keys (chmod 600)
Features:
- File permissions restricted to owner (600)
- Isolated from version control
- Encrypted at rest (via OS filesystem encryption)
- Never logged or printed
Best Practices
.api-keys to version controlls -la ~/.model-router/π Usage Examples
Example 1: Cost-Optimized Workflow
# Classify task first
python3 scripts/classify_task.py "Extract prices from this CSV"
# Result: simple task β use glm-4.5-air
sessions_spawn --task "Extract prices" --model glm-4.5-air
# Then analyze with better model if needed
sessions_spawn --task "Analyze price trends" --model claude-sonnet
Example 2: Progressive Escalation
# Try cheap model first (60s timeout)
sessions_spawn --task "Fix this bug" --model glm-4.5-air --runTimeoutSeconds 60
# If fails, escalate to premium
sessions_spawn --task "Fix complex architecture bug" --model claude-opus
Example 3: Parallel Processing
# Batch simple tasks in parallel with cheap model
sessions_spawn --task "Summarize doc A" --model glm-4.5-air &
sessions_spawn --task "Summarize doc B" --model glm-4.5-air &
sessions_spawn --task "Summarize doc C" --model glm-4.5-air &
wait
Example 4: Multimodal with Gemini
# Vision task with 2M token context
sessions_spawn --task "Analyze these 100 images" --model gemini-1.5-pro
π οΈ Configuration Files
~/.model-router/config.json
{
"version": "1.1.0",
"providers": {
"anthropic": {
"configured": true,
"models": ["claude-opus-4-5", "claude-sonnet-4-5", "claude-haiku-4-5"]
},
"openai": {
"configured": true,
"models": ["gpt-4o", "gpt-4o-mini", "o1-mini", "o1-preview"]
}
},
"task_mappings": {
"simple": "glm-4.5-air",
"coding": "claude-sonnet-4-5",
"research": "claude-sonnet-4-5",
"creative": "claude-opus-4-5"
},
"preferences": {
"cost_optimization": "balanced",
"default_provider": "anthropic"
}
}
~/.model-router/.api-keys
# Generated by setup wizard - DO NOT edit manually
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-proj-...
GEMINI_API_KEY=AIza...
π Version 1.1 Changes
New Features
- β Interactive setup wizard for guided configuration
- β Secure API key storage with file permissions
- β Task-to-model mapping customization
- β Multi-provider support (6 providers)
- β Cost optimization levels (aggressive/balanced/quality)
Improvements
- β Better task classification with confidence scores
- β Provider-specific model recommendations
- β Enhanced security with isolated storage
- β Comprehensive documentation
Migration from 1.0
Run the setup wizard to reconfigure:python3 scripts/setup-wizard.py
π Command Reference
Setup Wizard
python3 scripts/setup-wizard.py
Interactive configuration of providers, mappings, and preferences.
Task Classifier
python3 scripts/classify_task.py "your task description"
python3 scripts/classify_task.py "your task" --format json
Get model recommendation with reasoning.
List Models
python3 scripts/setup-wizard.py --list
Show all available models and their status.
π€ Integration with Other Skills
| Skill | Integration |
| model-usage | Track cost per provider to optimize routing |
| sessions_spawn | Primary tool for model delegation |
| session_status | Check current model and usage |
β‘ Performance Tips
π Troubleshooting
"No suitable model found"
- Run setup wizard to configure providers
- Check API keys are valid
- Verify permissions on
.api-keysfile
"Module not found"
pip3 install -r requirements.txt # if needed
Wrong model selected
sessions_spawn --modelπ Additional Resources
- Provider Docs:
- Setup: Run
python3 scripts/setup-wizard.py - Support: Check
references/folder for detailed guides