Skill UI

This guide provides a comprehensive reference architecture for building production-ready, enterprise-grade applications on Palantir Foundry. It covers the entire data lifecycle, detailing best practices for the standard data pipeline (Raw > Clean > Model), Ontology design, external API integration patterns, and robust multi-layered security models. Use it when designing, planning, or optimizing complex data infrastructure within Foundry.

This comprehensive guide provides blueprints for implementing optimal Snowflake data architectures. It covers diverse patterns, including traditional data warehouses, Lakehouse designs using Iceberg tables, decentralized Data Mesh structures, and advanced data sharing and Snowpark native patterns. Use this when designing enterprise data platforms across varying scales.

Provides comprehensive guidance for the full lifecycle management of semantic models (e.g., Power BI/Analysis Services). Use this skill when designing, building, optimizing, refreshing, or auditing data models. It guides the user through best practices, relationship management, measure creation, and model optimization (e.g., size reduction, Direct Lake setup), ensuring changes are routed through the most appropriate tool cascade (te CLI, TOM, or TMDL authoring).

This tool guides users through the critical process of designing experiments *before* data collection. It helps select appropriate structures—such as factorial, crossover, or blocked designs—to ensure that collected data is interpretable and allows for robust causal inference. Use it when planning scientific studies, assigning subjects, or optimizing responses across multiple factors.

This skill provides a structured framework for designing and implementing composable recommendation, ranking, and feed pipelines. It models the industry-standard six-stage pattern: Source, Hydrator, Filter, Scorer, Selector, and SideEffect. Use it for any system that selects "the top K items for a (user, context)", such as social feeds, ad ranking, RAG rerankers, or content recommendation engines, ensuring a robust and scalable architecture.