What happens if a provider like OpenAI goes down?

The skill includes a 'resilience' configuration that defines fallback chains, automatically rerouting your request to another provider like Anthropic or Google.

Is it possible to share configurations across a team?

The skill supports team-config files where shared providers can be defined while allowing individual members to use their own private API keys for specific models.

How does this skill help reduce AI costs?

It implements cost-aware routing that uses cheaper models for simple tasks like documentation and only escalates to expensive models when deep reasoning is required.

Does it support high-context models like Gemini 1.5 Pro?

Yes, it includes context management settings that automatically select models based on the size of the code context, supporting up to 1 million tokens.

Can I set a daily spending limit for my project?

Yes, the configuration supports budget tracking and will even auto-downgrade models once you reach a specific percentage of your daily budget.

Multi-Provider Model Orchestrator

Name: Multi-Provider Model Orchestrator
Author: monch1962

bymonch1962

•

Data Science & ML

Orchestrates multiple AI model providers to optimize development workflows for cost, latency, and reasoning capability.

The Multi-Provider Model Configuration skill provides a comprehensive framework for managing diverse AI models from OpenAI, Anthropic, and Google within the Opencode environment. It enables developers to intelligently route requests based on specific task requirements—such as code generation, debugging, or documentation—while maintaining strict cost controls through automated budget management and model downgrading. By implementing sophisticated fallback chains and context-aware selection, this skill ensures maximum reliability and efficiency, allowing teams to leverage the unique strengths of different LLMs without manual intervention.

Key Features

01Project and team-specific configuration inheritance

02Dynamic context window selection for large-scale codebases

03Cost-aware budget management and auto-downgrading

04Intelligent task-based routing for specialized model usage

05Multi-provider resilience with automated fallback chains

061 GitHub stars

Use Cases

01Configuring specific agents like architects or reviewers to use the most capable reasoning models available.

02Ensuring uptime during provider outages by automatically switching to secondary LLM services.

03Optimizing API spend by using cheaper models for routine documentation and high-tier models for complex logic.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add monch1962/everything-opencode multi-provider-models

For use in Claude.ai and ChatGPT

Download Skill