v1.1.0

Model Router

digitaladaption digitaladaption ← All skills

A comprehensive AI model routing system that automatically selects the optimal model for any task. Set up multiple AI providers (Anthropic, OpenAI, Gemini, Moonshot, Z.ai, GLM) with secure API key storage, then route tasks to the best model based on task type, complexity, and cost optimization. Includes interactive setup wizard, task classification, and cost-effective delegation patterns. Use when you need "use X model for this", "switch model", "optimal model", "which model should I use", or to balance quality vs cost across multiple AI providers.

Downloads
1.5k
Stars
3
Versions
2
Updated
2026-02-23

Install

npx clawhub@latest install model-router

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.

🎯 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

🚀 Quick Start

Step 1: Run the Setup Wizard

cd skills/model-router

python3 scripts/setup-wizard.py

The wizard will guide you through:

1. Provider setup - Add your API keys (Anthropic, OpenAI, Gemini, etc.)

2. Task mappings - Choose which model for each task type

3. Preferences - Set cost optimization level

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

📊 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 |

🎛️ 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 |

💰 Cost Optimization

Aggressive Mode

Always uses the cheapest capable model:

  • -Simple → glm-4.5-air (~10% cost)
  • -Coding → claude-haiku-4-5 (~25% cost)
  • -Research → claude-sonnet-4-5 (~50% cost)
Savings: 50-90% compared to always using premium models

Balanced Mode (Default)

Considers cost vs quality:

  • -Simple tasks → Cheap models
  • -Critical tasks → Premium models
  • -Automatic escalation if cheap model fails

Quality Mode

Always uses the best model regardless of cost

🔒 Security

API Key Storage

~/.model-router/

├── config.json # Model mappings (chmod 600)

└── .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

1. Never commit .api-keys to version control

2. Use environment variables for production deployments

3. Rotate keys regularly via the wizard

4. Audit access with ls -la ~/.model-router/

📖 Usage Examples

Example 1: Cost-Optimized Workflow

Classify task first

python3 scripts/classify_task.py "Extract prices from this CSV"

Result: simple task → 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

🛠️ 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...

🔄 Version 1.1 Changes

New Features

  • -Interactive setup wizard for guided configuration
  • -Secure API key storage with file permissions
  • -Task-to-model mapping customization
  • -Multi-provider support (6 providers)
  • -Cost optimization levels (aggressive/balanced/quality)

Improvements

  • -✅ Better task classification with confidence scores
  • -✅ Provider-specific model recommendations
  • -✅ Enhanced security with isolated storage
  • -✅ Comprehensive documentation

Migration from 1.0

Run the setup wizard to reconfigure:

python3 scripts/setup-wizard.py

📚 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.

🤝 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 |

⚡ Performance Tips

1. Start simple - Try cheap models first

2. Batch tasks - Combine multiple simple tasks

3. Use cleanup - Delete sessions after one-off tasks

4. Set timeouts - Prevent runaway sub-agents

5. Monitor usage - Track costs per provider

🐛 Troubleshooting

"No suitable model found"

  • -Run setup wizard to configure providers
  • -Check API keys are valid
  • -Verify permissions on .api-keys file

"Module not found"

pip3 install -r requirements.txt  # if needed

Wrong model selected

1. Customize task mappings via wizard

2. Use explicit model in sessions_spawn --model

3. Adjust cost optimization preference

📖 Additional Resources

  • -Provider Docs:
- [Anthropic](https://docs.anthropic.com)

- [OpenAI](https://platform.openai.com/docs)

- [Gemini](https://ai.google.dev/docs)

- [Moonshot](https://platform.moonshot.cn/docs)

- [Z.ai](https://api.z.ai/docs)

- [GLM](https://open.bigmodel.cn/dev/api)

  • -Setup: Run python3 scripts/setup-wizard.py
  • -Support: Check references/ folder for detailed guides

Launch an agent with Model Router on Termo.