Skill UI

Details the PBIP (Power BI Project) format, which converts the opaque PBIX binary into a clear, structured, and editable set of text files. This guide covers project structure, cross-cutting operations (like renaming and forking), and the technical differences between Thick and Thin reports, enabling better Git integration and multi-author collaboration.

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.

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.

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.

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 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.

A comprehensive reference guide covering advanced architectural design patterns crucial for modern, scalable distributed systems. Topics include CQRS, Event Sourcing, Saga, and Circuit Breaker, providing best practices for microservices migration and fault tolerance.

A comprehensive reference guide providing quantitative benchmarks and formulas for system architects. It covers user-to-RPS conversion, storage estimation, bandwidth calculation, known scale limits of major technologies (databases, queues, caches), and capacity planning for various user loads (1K DAU to 10M DAU). Essential for designing scalable, high-availability applications.

A detailed, comprehensive reference guide covering best practices for securing modern applications. This checklist spans network architecture, API design, data encryption, authentication protocols, and regulatory compliance (GDPR, HIPAA, PCI-DSS), ensuring robust security across the entire technology stack.

A comprehensive guide detailing the selection criteria for core modern system components, including databases (SQL/NoSQL), caching, message queues, and API protocols. It helps architects choose the optimal technology for specific use cases, scalability needs, and architectural patterns.

This skill guides coding agents through a comprehensive memory loop using AccInt's MCP server. It allows agents to retrieve prior outcomes, resolve complex reasoning frames, and formally close commitments with verifiable evidence (e.g., passing tests, successful merges). Essential for managing non-trivial, multi-step development workflows and ensuring work builds on genuine results.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.