Skill UI

A comprehensive guide for managing the entire lifecycle of tabular data models (Semantic Models) in Power BI/Analysis Services. It provides best practices and a tool cascade (CLI, TOM, TMDL) for designing, building, optimizing, refreshing, and auditing models. Use this skill when performing advanced model operations, optimizing performance, or ensuring data quality.

An interactive workflow designed to audit and standardize naming conventions within Power BI semantic models stored as TMDL files. It ensures that tables, columns, measures, and display folders adhere to consistent, human-readable, and business-aligned standards. The tool guides users through gathering critical business context before auditing and applying complex, cross-file reference updates to maintain data integrity.

This skill enables the generation of rich, inline SVG graphics directly within Power BI reports. By writing DAX measures that return SVG markup strings and setting the data category to ImageUrl, users can visualize complex charts (like sparklines, gauges, and progress bars) within standard visuals such as Tables, Cards, and Matrices. It guides users through the entire process, including recommended best practices like using existing UDF libraries and adhering to strict VAR-based DAX structures.

A comprehensive guide for searching documentation across multiple BI sources (TE docs, DAX.guide, SQLBI, Power BI/Fabric) using the pbi-search CLI. It also details the structure and use of critical configuration files, such as .tmuo, Preferences.json, and UiPreferences.json, essential for advanced data modeling and deployment.

A comprehensive guide to the Tabular Editor 2 command-line interface (CLI). It provides essential syntax and usage examples for automating data model management. Key functions include deploying models to XMLA endpoints, executing inline C# scripts, running Best Practice Analyzer (BPA), validating schemas, and integrating model processes into CI/CD pipelines in Windows environments.

This index serves as the central router and map for the comprehensive C-level advisory bundle. It structures high-stakes business processes by indexing 14 core C-suite roles (CEO, CFO, CTO, etc.), orchestration capabilities, and cross-cutting functions (e.g., board meetings, onboarding). It guides users on where to start for strategic planning, corporate governance, and complex decision-making.

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 comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.

This Main Agent acts as a central orchestrator for a specialized squad of AI agents, managing complex software development lifecycles. It guides projects through defined phases—from requirements gathering and planning to architecture, implementation, testing, and deployment. It maintains strict context discipline by summarizing agent outputs and referencing full artifacts, ensuring efficient, structured, and non-overwhelming communication to the user.

This skill transforms vague or high-level project ideas into eight comprehensive, interconnected planning documents (PRD, TechSpec, Design, Schema, etc.). It establishes a definitive, persistent source of truth for the project's scope, architecture, and design guidelines before a single line of code is written. Ideal for initiating brand-new software projects to prevent scope creep and planning gaps.

An advanced ruleset for crafting clear, precise, and formal English technical prose. This guide integrates established literary principles (like those from Strunk & White and Orwell) with modern best practices for AI-generated content. It is ideal for writing research papers, technical documentation, proposals, and release notes, ensuring maximum clarity and professional tone.

This guide helps developers audit and clean up Vite + React projects initialized using the Lovable scaffolding tool. It systematically removes all boilerplate artifacts, including placeholder assets, dedicated dependencies (like lovable-tagger), generated documentation, and unnecessary components (e.g., unused Radix deps). The goal is to deliver a clean, fully owned, and production-ready codebase.