Skill UI

A comprehensive guide for using C# scripting within Tabular Editor to programmatically manipulate and automate Power BI semantic models. This skill supports bulk metadata operations, creating calculation groups, managing security roles, and advanced data model restructuring using the TOM API and LINQ.

This skill provides comprehensive guides and references for writing, debugging, and systematically optimizing DAX formulas within semantic models. It covers advanced topics including systematic performance optimization workflows, engine internals (like xmSQL), and best practices for both local (Power BI Desktop) and remote (Fabric/XMLA) model environments, ensuring efficient data calculation and query performance.

This skill provides comprehensive, expert guidance for utilizing the Fabric Command Line Interface (CLI) using the `fab` tool. It enables programmatic interaction with the entire Fabric and Power BI service cloud environment, including workspaces, semantic models, data assets, and configurations. Use it to automate tasks like authentication, metadata retrieval, data querying (DAX, T-SQL, DuckDB), and resource management, ensuring best practices and error handling are maintained.

This guide provides comprehensive instructions for searching Tabular Editor (TE) documentation and understanding complex configuration files. It details the usage of the `pbi-search` CLI tool, allowing users to query multiple sources (DAX, Power BI, SQLBI) simultaneously. It also covers the structure and best practices for model-specific files like `.tmuo` and application preferences, ensuring efficient data modeling and development.

Provides a comprehensive CLI reference for Tabular Editor 2 (TE2). It enables automated model management, including deployment to XMLA endpoints, running embedded scripts, performing Best Practice Analysis (BPA), and handling model exports (TMDL). This skill is essential for integrating data model lifecycle management into CI/CD pipelines and automating repetitive tasks from the command line.

This advanced tool surfaces critical, often unrecorded, evidence of human-AI collaboration during development sessions. It analyzes git diffs and conversational context across multiple layers to classify the signal level (HIGH/MEDIUM/LOW), measure technical complexity, detect decision forks, and quantify the specific contribution of the AI model, providing structured data for post-session retrospectives and accountability.

Aria functions as a System Architect, responsible for establishing the definitive structural foundation of the entire system. She designs comprehensive blueprints covering the data model (schema, relationships, constraints), API contract specifications (endpoints, auth, pagination), modular file structure, and selection of core architectural design patterns. Her output ensures that no code is written without a rigorously defined, approved architectural plan, minimizing ambiguity and technical debt.

This skill guides you through a comprehensive, multi-phase interview to capture every necessary detail of a new project idea. It is designed to run BEFORE any code is written, forcing detailed specification gathering across purpose, features, data models, and technical constraints. The output is a clean, self-contained prompt.md file, ensuring subsequent development is based on solid, unambiguous requirements and preventing costly mistakes.

This comprehensive guide details idiomatic best practices for writing high-performance, safe code in Rust. It covers advanced topics such as understanding Ownership and Borrowing rules, robust error handling using the '?' operator, optimizing functional programming with Iterators, implementing structured concurrency, and defining robust data models with Structs and Enums.

This skill generates comprehensive, production-ready database schema documents. It covers Entity-Relationship (ER) diagrams, detailed SQL DDL definitions, constraint analysis, index strategies, and access pattern optimization. Use it when designing a new database, documenting an existing one, or modeling complex data relationships for engineering review.

A comprehensive template designed to structure complex technical specifications, ensuring a complete record of engineering decisions. It guides users to document problem statements, proposed solutions, system architecture, data models, API designs, security considerations, and rollout plans, bridging product requirements and technical implementation.

This skill provides comprehensive security auditing for Model Context Protocol (MCP) servers and their associated tool metadata. It is designed to detect sophisticated supply chain attacks, including tool poisoning (indirect prompt injection), Server-Side Request Forgery (SSRF), tool shadowing, and unauthenticated exposure. It is essential for securing AI agent stacks before integrating new tools or during CI/CD processes.