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ax-ai

Generate TypeScript AI provider integration code using @ax-llm/ax.

1|1|Updated Mar 27, 2026
Search Tags:#typescript#ai#configuration#codegen#provider#ax-llm
One-click install
npx skills add https://github.com/jadecli/researchers --skill ax-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ax-ai
Source: https://github.com/jadecli/researchers/tree/main/agentcrawls-ts/.claude/skills/ax-ai
Command: npx skills add https://github.com/jadecli/researchers --skill ax-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps developers quickly generate robust AI provider integration code using @ax-llm/ax, reducing boilerplate and avoiding misconfigurations.

Core Features & Use Cases

  • Quick AI provider code generation for multiple providers (OpenAI, Anthropic, Google Gemini, Azure OpenAI, Groq, etc.)
  • Support for common workflows: chat, embeddings, presets, context caching, and MCP integration
  • Real-world use: scaffold provider configuration and common patterns in a ready-to-run TypeScript snippet

Quick Start

Generate a ready-to-use TypeScript snippet configuring an AI provider with apiKey and optional settings using @ax-llm/ax.

Frequently Asked Questions about ax-ai

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

FAQPage Schema
How do I generate TypeScript code for configuring multiple AI providers like OpenAI and Anthropic?▼

You can generate ready-to-run TypeScript snippets for AI provider configuration using the @ax-llm/ax library's ai() factory. It supports OpenAI, Anthropic, Google Gemini, and Azure OpenAI with safe production defaults.

What is the best way to set up AI chat and embeddings in TypeScript without writing boilerplate?▼

Using the @ax-llm/ax ai() factory is the best way to set up AI chat and embeddings. It automatically applies best practices, reducing boilerplate and avoiding misconfigurations for common workflows.

Can I use @ax-llm/ax to configure context caching and presets for Google Gemini?▼

Yes, @ax-llm/ax supports configuring context caching and presets for Google Gemini. The generated TypeScript code covers these common patterns alongside chat and embeddings integrations.

Does this AI provider code generation approach support Groq and Azure OpenAI out of the box?▼

Yes, AI provider code generation with @ax-llm/ax supports Groq and Azure OpenAI out of the box. It provides ready-to-use TypeScript snippets with API key configuration and optional settings for these providers.

Why should I use the ai() factory for AI provider integration instead of manual configuration?▼

You should use the ai() factory for AI provider integration because it implements best practices by default. This approach prevents misconfigurations and eliminates boilerplate when scaffolding provider setups.

How do I scaffold MCP integration when configuring AI providers in TypeScript?▼

You can scaffold MCP integration by generating TypeScript configuration code with @ax-llm/ax. The library supports MCP integration alongside common workflows like chat, embeddings, and context caching.

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