openrouter

Access and manage over 100 AI models via an OpenAI-compatible API.

6|2|Updated Jan 22, 2026
One-click install
npx skills add https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric --skill openrouter-fgarofalo56
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: openrouter
Source: https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric/tree/main/.github/skills/openrouter
Command: npx skills add https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric --skill openrouter-fgarofalo56

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, and includes references (resource) components.

What problem does it solve?

This Skill simplifies access to a vast array of AI models from multiple providers through a unified API, abstracting away the complexities of individual provider integrations and enabling cost-effective, flexible AI application development.

Core Features & Use Cases

  • Multi-Provider Access: Connect to over 100 AI models from providers like OpenAI, Anthropic, and Google.
  • Cost Management: Monitor and control spending with per-request limits and usage tracking.
  • Provider Routing & Fallbacks: Intelligently route requests to preferred providers or use fallbacks for resilience.
  • Use Case: Develop an application that dynamically selects the best AI model for a given task based on cost, performance, or specific features, ensuring optimal resource utilization and user experience.

Quick Start

Use the openrouter skill to get a response from the claude-3.5-sonnet model with the message "Hello!".

Frequently Asked Questions about openrouter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I access multiple AI models from OpenAI, Anthropic, and Google through one API?

You can access over 100 AI models from providers like OpenAI, Anthropic, and Google through a unified, OpenAI-compatible API. This abstracts away individual provider complexities, allowing flexible integration with function calling, streaming, and asynchronous operations.

What is the best way to manage LLM API spending across different providers?

To manage LLM API spending across providers, you can use built-in cost management features that monitor usage and enforce per-request spending limits. This ensures cost-effective resource utilization when dynamically selecting models for specific tasks.

Can I use the openai Python library to route requests to Claude and other non-OpenAI models?

Yes, you can use the openai dependency to route requests to non-OpenAI models. The system provides intelligent provider routing and fallback mechanisms, allowing you to send requests to preferred providers or automatically switch for resilience.

How do I build an application that dynamically selects the best AI model for a specific task?

You can build multi-model AI applications that dynamically select the best model based on cost, performance, or specific features. The unified interface supports intelligent routing and fallbacks to ensure optimal resource utilization and user experience.

Does this multi-provider LLM interface support asynchronous operations and streaming?

Yes, the multi-provider LLM interface supports asynchronous operations, streaming, and function calling. These features facilitate flexible integration when developing applications that require real-time responses or concurrent model requests.

When should I use a unified API interface instead of direct provider integrations for AI models?

Use a unified API interface instead of direct integrations when you need to access over 100 models across multiple providers while managing costs and ensuring resilience. It abstracts away individual provider complexities and provides intelligent fallback mechanisms.