Maintains and updates AI model registries including pricing, context windows, and provider capabilities.
The Model Registry Maintainer is a specialized skill designed to manage the lifecycle of LLM metadata within application backends. It provides structured workflows for adding new models, updating token pricing, and managing context window limits across systems like MassGen. By integrating with live data sources like LiteLLM and OpenRouter, this skill ensures that your application's model catalog remains accurate, enabling precise cost estimation, feature validation, and up-to-date documentation for the latest releases from OpenAI, Anthropic, Google, and other major providers.
Key Features
01Support for tracking release dates, vision capabilities, and tool-use features
02Integration guidance for LiteLLM and OpenRouter pricing databases
0381 GitHub stars
04Standardized workflows for updating Python-based model registries and token managers
05Automated validation through pre-defined pytest commands
06Documentation regeneration scripts for maintaining backend tables
Use Cases
01Synchronizing internal pricing tables with the latest official API costs
02Updating context window limits and output token caps for existing models
03Adding support for newly released LLMs like GPT-5 or Claude 4 variants
