rig-provider

What problem does it solve?

This Skill provides a comprehensive checklist and reference implementation for integrating new Large Language Model (LLM) providers into the Rig framework, ensuring compatibility and adherence to best practices.

Core Features & Use Cases

• Provider Implementation Guide: Detailed steps for creating new Rig model providers, covering essential components like structs, trait implementations, and capability declarations.
• API Alignment: Emphasizes keeping request/response fields consistent with upstream provider APIs.
• Error Handling & Telemetry: Guides on implementing robust error mapping and adding telemetry spans.
• WASM Compatibility: Provides patterns for ensuring Rig works seamlessly in WebAssembly environments.
• Prompt Hooks: Explains how to use prompt hooks for observing and controlling the agent's execution lifecycle.
• Quality Gates: Outlines critical requirements for code quality, including trait bounds, error handling, comments, and documentation.
• Use Case: A developer needs to add support for a new LLM API (e.g., "AwesomeLLM") to Rig. They would use this Skill to follow the established pattern, ensuring the integration is robust, efficient, and maintainable.

Quick Start

Use the rig-provider skill to implement a new Rig model provider following the OpenAI reference implementation pattern.