genai-integration

What problem does it solve?

Designing GenAI integrations is complex and often error-prone without a structured approach. This skill provides expert guidance for model selection, prompt engineering, and end-to-end pipelines (including RAG and embeddings), along with cost controls and observability to ensure robust, compliant deployments.

Core Features & Use Cases

• Model selection guidance based on cost, latency, context length, and compliance needs.
• Prompt template design (system, developer, user layers) with explicit output schemas.
• RAG and embeddings pipeline design, including chunking strategies and vector store considerations.
• End-to-end workflows for agent use cases, tooling steps, and fallback logic.
• Cost optimization strategies (caching, batching, tiering) with validation and observability integrations.
• Validation, testing, and safety guardrails to prevent prompt injection and unsafe operations.

Quick Start

Provide a concrete GenAI integration plan for a sample app and begin implementing the recommended prompts, pipelines, and observability checks.