Skill UI

This tool provides a read-only view over per-turn decision logs, aggregating data on skill co-occurrence patterns, meta-skill usage statistics, and router fixtures. It returns a structured JSON summary, making it ideal for analyzing historical skill usage, optimizing workflows, and feeding insights into downstream LLM models.

This skill provides expert, guided assistance for creating, auditing, and improving Best Practice Analyzer (BPA) rules for Power BI semantic models. It utilizes an interactive, double-diamond discovery process to gather deep context about your organizational standards, model structure, and business goals before generating tailored, reusable data validation and governance rules.

Provides expert guidance for connecting to Power BI Desktop's local tabular model using the Tabular Object Model (TOM) and ADOMD.NET via PowerShell. This skill covers model enumeration, executing DAX queries, metadata modification (tables, measures, relationships), query tracing, and model refreshing. It is specifically designed for managing the underlying data model structure when external tools like Tabular Editor CLI are unavailable.

This skill provides a comprehensive, step-by-step workflow for building complete Power BI reports from scratch using the pbir CLI. It guides users through model discovery, defining design briefs, visual layout, data validation, and final publishing. Ideal for automating the entire business intelligence (BI) reporting process and ensuring adherence to professional design standards.

This tool analyzes and maps the downstream dependencies of a semantic model across multiple Fabric workspaces. It is crucial for performing impact assessments before making modifications, auditing connected reports, or mapping cross-workspace data flows. It automates the lineage discovery process, providing comprehensive visibility into which reports rely on a specific data source.

A comprehensive guide to authoring, optimizing, and validating Power Query M expressions used within semantic model partitions. This resource covers crucial topics such as maintaining query folding for performance, applying early filtering and column pruning, and leveraging the Power Query API for robust data validation and debugging.

A comprehensive guide and API wrapper for triggering, monitoring, and validating semantic model refreshes in Power BI/Fabric. It supports various refresh types (full, data-only, calculate-only, etc.), enabling granular control over data reloading, recalculation, and performance troubleshooting using the Fabric CLI and Enhanced Refresh API.

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).

An interactive workflow for auditing and standardizing naming conventions (tables, columns, measures) in Power BI semantic models (TMDL). It ensures names are human-readable, consistent, and aligned with core business terminology, addressing technical issues like abbreviations, mixed casing, and inappropriate technical prefixes.

The Tabular Editor CLI (`te`) is a cross-platform, command-line utility for managing the entire lifecycle of semantic models (TMDL/BIM). It allows users to scaffold, inspect, validate, deploy, refresh, test, and query data models against various services, including Power BI, Fabric, and Azure AS, directly from the terminal. Ideal for automated workflows and CI/CD pipelines.

Perform a priori power analysis to determine required sample sizes for studies. Supports closed-form calculations for t-tests, ANOVA, and regression, plus Monte Carlo simulations for complex models like mixed models and survival analysis. Helps justify sample sizes for grants and protocols by calculating minimum detectable effects and power curves.

This skill guides the design of statistically rigorous A/B tests for optimizing product features, UI/UX changes, onboarding flows, and pricing models. It generates a complete test plan, including formulating hypotheses, calculating required sample sizes, estimating test duration, defining primary and guardrail metrics, and providing a detailed guide on interpreting results (ship, iterate, or reject).