Openclaw-master-skills ai-model-router

Intelligent AI model router that automatically switches between two configured models (local for simple tasks, cloud for complex ones). Detects local models (Ollama, LM Studio) automatically, routes based on task complexity and privacy. Use when users ask to "switch model", "use local/cloud model", or mention API keys/passwords (triggers privacy mode). Trigger on: sensitive data detection (forces local), complex tasks like "design architecture" (uses cloud), or configuration requests.

install

source · Clone the upstream repo

git clone https://github.com/LeoYeAI/openclaw-master-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/LeoYeAI/openclaw-master-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/ai-model-router-v2" ~/.claude/skills/leoyeai-openclaw-master-skills-ai-model-router && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/LeoYeAI/openclaw-master-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/ai-model-router-v2" ~/.openclaw/skills/leoyeai-openclaw-master-skills-ai-model-router && rm -rf "$T"

manifest: skills/ai-model-router-v2/SKILL.md

AI Model Router

Compact, intelligent model routing that just works.

Quick Start

# Install
npx clawhub@latest install ai-model-router

# First run - auto-detects your models
python3 skill/core/router.py "What is Python?"

# List available models
python3 skill/core/router.py --list

How It Works

Your Request → Analyze → Select Model
                          ↓
                    Simple? → Primary (fast/cheap)
                    Complex? → Secondary (capable)
                    Private? → Primary (forced)

Scoring (from model-router-premium)

Pattern	Points
Microservices, architecture	+10
Design, implement, optimize	+5
Explain, analyze, compare	+3
Syntax, example, "what is"	-3

Threshold: 5 (simple vs complex)

Features

Feature	Status
Auto-detect local models	✓ (Ollama, LM Studio)
Cloud model registry	✓ (7 built-in)
Privacy detection	✓ (API keys, passwords)
Context tracking	✓ (conversations)
JSON config	✓ (optional)
CLI interface	✓
Core code size	~200 lines

CLI

# Route a task
python3 skill/core/router.py "Design a system"
python3 skill/core/router.py "What is a for loop?"

# Options
--json                    # JSON output
--force primary           # Force primary model
--list                    # List all models
--status                  # Show status

Python API

from skill.core.router import RouterCore

router = RouterCore()
result = router.route("Design microservices")

print(result.model_name)   # "Claude Opus 4"
print(result.reason)        # "complex_task(score=15)"
print(result.confidence)    # 0.75

Configuration (Optional)

Create

~/.model-router/models.json

{
  "primary_model": {"id": "ollama:llama3:8b"},
  "secondary_model": {"id": "anthropic:claude-opus-4"},
  "models": [...]
}

Without config: Auto-detects local + uses cloud registry.

Privacy Protection

Automatically forces primary (local) when sensitive data detected:

API keys (
```
sk-...
```
,
```
api_key
```
)
Passwords (
```
password
```
,
```
passwd
```
)
Tokens (
```
bearer
```
,
```
secret
```
)
Emails, SSN, credit cards

Files

```
core/router.py
```
- Core routing engine (~200 lines)
```
modules/detector.py
```
- Auto-detection (optional)
```
modules/context.py
```
- Context tracking (optional)

Inspired By

model-router-premium: Simple scoring logic, cost-aware routing
Model Router v1: Full feature set, documentation

This version combines:

The simplicity of model-router-premium (~200 lines)
The features of ai-model-router (privacy, auto-detect, context)