llm-app-patterns

What problem does it solve?

This Skill provides production-ready patterns to accelerate the design, development, and deployment of LLM-powered applications. It helps teams avoid reinventing core patterns and promotes consistency across projects.

Core Features & Use Cases

• RAG Pipeline Architecture: guidance on ingestion, embedding, retrieval, and generation with practical examples.
• Agent Architectures: patterns like ReAct, Function Calling, Plan-and-Execute, and Multi-Agent collaboration.
• Prompt IDEs & Versioning: templates, variables, versioning, and chaining prompts to streamline development.
• LLMOps & Observability: metrics, logging, tracing, and evaluation frameworks to monitor production systems.
• Production Patterns: caching, rate limiting, and fallback strategies to improve reliability.
• Use Case: architect end-to-end AI assistants, enterprise knowledge bases, and automated data-processing pipelines.

Quick Start

Start by selecting a RAG pattern for your data, implement a compatible agent pattern for the task, wire up a prompt template, and enable LLM observability to begin iterative improvement.