From sundial-org-awesome-openclaw-skills-4
Routes AI model requests across multiple providers (Anthropic, OpenAI, Gemini, etc.) selecting the optimal model based on task type, complexity, and cost. Includes setup wizard and task classifier.
How this skill is triggered — by the user, by Claude, or both
Slash command
/sundial-org-awesome-openclaw-skills-4:model-routerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Intelligent AI model routing across multiple providers for optimal cost-performance balance.**
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.
cd skills/model-router
python3 scripts/setup-wizard.py
The wizard will guide you through:
# 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
# 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
| 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 |
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 |
Always uses the cheapest capable model:
Savings: 50-90% compared to always using premium models
Considers cost vs quality:
Always uses the best model regardless of cost
~/.model-router/
├── config.json # Model mappings (chmod 600)
└── .api-keys # API keys (chmod 600)
Features:
.api-keys to version controlls -la ~/.model-router/# 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
# 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
# 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
# Vision task with 2M token context
sessions_spawn --task "Analyze these 100 images" --model gemini-1.5-pro
~/.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...
Run the setup wizard to reconfigure:
python3 scripts/setup-wizard.py
python3 scripts/setup-wizard.py
Interactive configuration of providers, mappings, and preferences.
python3 scripts/classify_task.py "your task description"
python3 scripts/classify_task.py "your task" --format json
Get model recommendation with reasoning.
python3 scripts/setup-wizard.py --list
Show all available models and their status.
| 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 |
.api-keys filepip3 install -r requirements.txt # if needed
sessions_spawn --modelnpx claudepluginhub joshuarweaver/cascade-ai-ml-agents-misc-2 --plugin sundial-org-awesome-openclaw-skills-4Implements task-based and complexity-based model routing on OpenRouter to optimize cost, quality, and latency across 100+ models.
Routes AI tasks to optimal LLMs by analyzing budget, deployment (local/cloud), and modality (text/vision/coding). Fetches live model data via curl and runs Python router script.
Model routing configuration templates and strategies for cost optimization, speed optimization, quality optimization, and intelligent fallback chains. Use when building AI applications with OpenRouter, implementing model routing strategies, optimizing API costs, setting up fallback chains, implementing quality-based routing, or when user mentions model routing, cost optimization, fallback strategies, model selection, intelligent routing, or dynamic model switching.