AI Data Integration Skill for Claude

Expert guidance for integrating AI/LLM capabilities with data engineering systems. Covers MCP server patterns for warehouses, NL-to-SQL generation, LLM-powered data transformations, and embeddings for data discovery. Security tiers are deeply integrated -- not bolted on.

Not an ML/MLOps skill. Covers how AI agents interact with data platforms, not model training or deployment.

When to Use

Activate when: building MCP servers for warehouse data, implementing NL-to-SQL interfaces, using LLMs for data enrichment/classification/extraction in pipelines, building embeddings for catalog search or semantic matching, designing AI agent access with security guardrails, evaluating when AI adds value vs traditional approaches.

Don't use for: ML model training/experiment tracking, general prompt engineering, chatbots/conversational AI, dbt/DLT/orchestration (use domain skills), Python DataFrame transforms without LLM involvement (python-data-engineering-skill).

Scope Constraints

• This skill generates integration patterns, not production-ready applications.
• All code examples assume read-only warehouse access unless explicitly stated.
• Security guidance covers AI-specific concerns only -- see Security & Compliance Patterns for the full framework.
• Cost estimates are approximate and vary by provider and model version.