An intelligent multi-model routing manager that optimizes AI performance and reduces costs through automated model selection and failover logic.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install model-router-manager
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install model-router-manager using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Model Router Manager?
Model Router Manager is a sophisticated tool designed to manage multiple AI models seamlessly within your workflow. By establishing a model chain consisting of a primary model and multiple tiered fallbacks, it ensures that your AI agents remain operational even if a specific provider experiences downtime or latency. This skill is a vital component for developers looking to scale their Openclaw Skills while maintaining high reliability and cost efficiency.
The manager allows users to define routing strategies based on three main pillars: cost, speed, and quality. Whether you need the most economical model for routine tasks or the highest quality output for complex coding, the router automatically handles the transition. With built-in cost monitoring and real-time statistics, it provides full visibility into model usage and budget management, ensuring that every request is handled by the most appropriate engine.
Model Router Manager Use Cases
- Automated failover to backup models during API outages or rate limiting scenarios.
- Cost-optimization by routing simple tasks to cheaper models while reserving premium models for complex logic.
- Performance-tuning by selecting the fastest available model for time-sensitive applications.
- Task-specific routing for specialized coding or vision-based AI workloads using Openclaw Skills.
- Budget enforcement through daily cost limits and real-time spending alerts.
How Model Router Manager Works
- Define a model chain by configuring a primary provider and at least two fallback alternatives.
- Select a routing strategy such as cost, speed, or quality to dictate how models are prioritized.
- The router intercepts incoming requests and evaluates the best available model according to the active strategy.
- If the primary model fails or times out, the system automatically switches to the next fallback within 1-2 seconds.
- Usage data and costs are logged in real-time, providing actionable insights through a statistics dashboard.
Model Router Manager Setup
To install and configure the Model Router Manager for your Openclaw Skills, ensure Node.js is installed. Begin by setting up your model chain:
# Configure primary and fallback models
model-router config \
--primary kimi-coding/k2p5 \
--fallback-1 bailian/qwen3-max-2026-01-23 \
--fallback-2 openrouter/gpt-4o
Next, apply your desired routing strategy:
model-router strategy cost
You can verify the configuration and monitor statistics using:
model-router stats
Model Router Manager Data Schema & Taxonomy
The skill utilizes a structured JSON configuration to manage model hierarchies and budget constraints. Below is the primary data schema:
| Property | Type | Description |
|---|---|---|
| strategy | String | The active routing logic (cost, speed, or quality). |
| primary | String | The identifier for the default model provider. |
| fallbacks | Array | A prioritized list of backup models. |
| costLimit | Object | Contains daily budget values and alert percentage thresholds. |
| stats | Object | Historical data tracking calls, savings, and latency. |
Model Router Manager Advanced Features
- Task-specific routing via CLI to assign specialized models to coding or vision tasks.
- Seamless API integration for direct use within JavaScript and Node.js applications.
- Local model fallback capabilities to maintain service during complete external API outages.
- Intelligent timeout management with configurable thresholds to accelerate failover transitions.
- Granular cost monitoring with automated alerts when spending reaches a predefined limit.
SKILL.md
Loading
Related Openclaw Skills
RTFM Testing
RTFM Testing is a methodology that spawns fresh AI agents with zero context to validate whether documentation is actually usable for its intended tasks.
Bagman
Bagman is a comprehensive security framework for AI agents to manage private keys and API secrets without risking accidental exposure or theft.
Bagman
Bagman is a secure key management framework for AI agents to handle wallets, API secrets, and private keys safely.
Agentic Money
A decentralized protocol skill enabling AI agents to discover, hire, and receive payments for services via Ethereum-based escrow.
Content Moderation Skill
A two-layer safety framework designed to protect AI agents from prompt injections and sensitive content violations.
PDF Watermark Tool
A smart PDF utility that automatically detects page orientation to apply perfectly centered, adjustable text watermarks.
Featured*
