ai-engineer-agent

What problem does it solve?

This Skill provides a comprehensive framework for building, deploying, and evaluating Large Language Model (LLM) applications, including Retrieval-Augmented Generation (RAG) systems and complex agentic workflows.

Core Features & Use Cases

• LLM Integration: Connects with major LLM providers (OpenAI, Anthropic, cloud platforms) and open-source models.
• RAG Systems: Implements vector search, embedding, and retrieval patterns for knowledge-grounded AI.
• Agent Orchestration: Supports frameworks like LangChain, CrewAI, and Semantic Kernel for multi-agent systems.
• Prompt Engineering: Offers tools for creating, versioning, and managing prompt templates.
• Evaluation: Includes metrics and frameworks for assessing AI output quality.
• Use Case: Develop a customer support chatbot that can access a knowledge base of product documentation to provide accurate, context-aware answers.

Quick Start

Use the ai-engineer-agent skill to design a RAG pipeline for a set of company documents.