Skill UI

A comprehensive reference for the Power BI Enhanced Report (PBIR) JSON format. This skill details the structure of report metadata, including visual configurations (visual.json), report-level settings, theme inheritance, and complex formatting rules. It is essential for developers needing to read, interpret, or programmatically interact with the internal workings and schema of Power BI reports.

This skill provides expert guidance on Public Relations (PR) and maximizing earned media for software products. It teaches the philosophy of successful pitching, focusing on identifying strong stories (trends, data, human narrative) rather than just the product. Learn four modes of outreach—reactive newsjacking, proactive pitching, inbound requests, and owned assets—to build brand legitimacy, backlinks, and industry authority from journalists and publications.

The te CLI is a cross-platform, self-contained binary providing expert guidance for managing, validating, and deploying semantic models (BIM/TMDL). It enables users to perform complex data operations—such as scaffolding, inspecting, editing DAX, running BPA, querying, and refreshing models—entirely from the terminal, making it essential for CI/CD pipelines and automated data workflows.

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.

Provides expert guidance for authoring and editing Tabular Model Definition Language (TMDL) files directly within PBIP projects. This skill is useful for making quick text-level fixes (like descriptions, format strings, or adding measures) when specialized tools (like Tabular Editor CLI or Power BI Desktop) are unavailable, especially for Git workflow or manual adjustments.

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.

A dedicated tool for querying Lark Meeting Notes (Notes) details and raw verbatim transcripts. It requires an explicit note_id to function, allowing users to determine the display type, access associated document tokens, and retrieve the original unified transcript. It strictly focuses on note-based retrieval and does not handle searching by title, document body, or meeting ID.

This skill maps engineering changes (code diffs, architecture designs, IaC) to specific financial compliance controls, such as PCI-DSS v4.0 and MAS TRM. It generates an auditable report detailing compliance gaps, required evidence, and concrete remediation steps, helping teams catch violations before formal audits.

Mason is the dedicated builder agent responsible for writing clean, functional, and production-ready code. He strictly adheres to architectural blueprints and defined checklists, ensuring every feature is implemented with high code quality standards, including comprehensive error handling, security best practices, and testability. Ideal for the core development phase of complex projects.

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.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.