What is the difference between the model tiers?

Fast models are for surface-level issues, Balanced models provide the best quality-to-cost ratio for standard reviews, and Thorough models are used for deep architectural and security analysis.

Does this skill require specific CLI tools?

Yes, it checks for the availability of provider-specific CLIs like 'gemini', 'claude', or 'pi' to fetch the latest available models.

How often should I run the Update Provider Models skill?

It is recommended to run this skill once a month or whenever you hear announcements regarding new model releases from AI providers.

Which AI providers does this skill support?

This skill supports a wide range of providers including Google Gemini, OpenAI Codex, GitHub Copilot, Cursor Agent, OpenCode, Anthropic Claude, and Pi.

AI Provider Model Updater

Name: AI Provider Model Updater
Author: in-the-loop-labs

byin-the-loop-labs

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Collaboration Tools

Synchronizes and updates built-in model configurations for various AI providers to ensure access to the latest LLM capabilities for code review.

The Update Provider Models skill automates the maintenance of the pair-review tool's AI engine by scanning for new model releases from major providers like Anthropic, Google, and OpenAI. It guides users through the process of verifying CLI availability, discovering new model IDs, and categorizing them into performance-optimized tiers—Fast, Balanced, and Thorough. This ensures that the AI-assisted code review process always utilizes the most current, cost-effective, and capable models while maintaining codebase integrity through automated test verification.

Key Features

01Source code automation for updating provider files and JSDoc comments

02Multi-provider support including Gemini, Codex, Copilot, Cursor, and Claude

0316 GitHub stars

04Tiered model categorization (Fast, Balanced, Thorough) for cost-performance optimization

05Post-update verification using integrated test suites

06Automated model discovery via provider CLIs and web documentation

Use Cases

01Optimizing API costs by switching to newer 'Flash' or 'Mini' model variants

02Updating the review tool immediately after a major LLM release announcement

03Adding experimental or preview models to the local development environment

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add in-the-loop-labs/pair-review update-provider-models

For use in Claude.ai and ChatGPT

Download Skill