Skill UI

This skill provides comprehensive guidance and established patterns for conducting rigorous scientific research and complex data analysis. It helps users structure their thinking process, ensuring a systematic and methodical approach to scholarly inquiry. Ideal for academic projects, literature reviews, and complex data interpretation.

This comprehensive guide identifies and explains common anti-patterns, gotchas, and integration mistakes when using Clay's data enrichment platform. It details the root causes of credit waste, workflow failures, and data loss, providing actionable fixes for auditing configurations, onboarding new team members, or optimizing existing pipelines.

Provides comprehensive monitoring for the Clay data enrichment pipeline. It tracks critical operational metrics such as credit consumption velocity, enrichment success rates (hit rates), data quality scores, and lead distribution. Essential for cost control and ensuring pipeline health in data-intensive CRM workflows.

A comprehensive system for implementing policy guardrails in data enrichment pipelines. It enforces critical controls including credit spending limits, blocks the enrichment of sensitive PII (e.g., SSN, bank details), and validates input data quality. Essential for maintaining compliance (GDPR/CCPA) and managing costs when processing large volumes of personal and business data.

This comprehensive checklist guides users through validating and preparing Clay enrichment pipelines for a production launch. It covers critical areas including table schema finalization, data quality gates (validation, deduplication), credit cost management, webhook reliability testing, and establishing robust monitoring and alerting procedures before going live.

Builds AutoML pipelines by analyzing user requests, generating code for data preparation, model selection, hyperparameter tuning, validation, and metrics, then documenting artifacts for streamlined automated machine learning workflows.

Generates Python code and workflows for collaborative, content-based, or hybrid recommendation models, handling data prep, training, evaluation, and scalability so Claude can deliver tailored suggestions across domains.

This comprehensive skill simulates an expert business analyst, specializing in transforming complex raw data into actionable, strategic insights. The scope covers modern Business Intelligence (BI) platforms (Tableau, Power BI), AI-powered predictive modeling, designing robust KPI/OKR frameworks, advanced financial modeling, and optimizing business processes. It is designed for users needing to drive data-driven decision-making and create executive-level reports.

Provides automated, industry-standard guidance and code for complex SQL joins, visualizations, and BI analyses whenever the “complex join helper” skill is invoked in a data analytics context.

Guides users through compression optimizer scenarios within data pipelines, offering best practices, code templates, and validation steps for ETL, transformation, and streaming workflows.

Automates correlation analyzer workflows by offering best-practice guidance, executable SQL, visualization tips, and statistical validation for data analytics requests.

Transforms raw datasets into charts, plots, and graphs by analyzing structure, picking suitable visualization types, and rendering them clearly so users can request visualizations or explore patterns and relationships.