Skill UI

This skill serves as an alias for the comprehensive debugging toolkit, enabling users to perform smart, guided debugging sessions. It assists in identifying errors, improving code quality, and walking through complex technical processes. Use it when you need structured help with debugging code in a defined environment.

This guide outlines a systematic workflow to eliminate copy-paste duplication (code clones) detected by tools like jscpd. It teaches developers how to refactor repeated code into shared functions, modules, constants, or base classes. Use this process when your codebase exhibits significant redundancy to improve maintainability, reduce technical debt, and enhance overall code quality.

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.

This guide details how to integrate R code, primarily using the powerful ggplot2 library, into Power BI reports. It enables the creation of advanced, static, and publication-quality statistical visualizations. The process covers the technical workflow, including setting up the JSON structure, writing the mandatory R script (e.g., using `print(p)`), handling data injection, and adhering to best practices for professional BI reporting.

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 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 skill generates a formal Architecture Decision Record (ADR) following industry-standard formats. It guides users through documenting the full rationale behind significant technical choices, ensuring that the context, alternatives considered, chosen option, and resulting trade-offs are all captured. Ideal for maintaining architectural integrity and knowledge transfer within engineering teams.

A comprehensive guide and playbook for managing feature flags across services or teams. It covers flag taxonomy (Release, Experiment, Ops, Permission), naming conventions, safe rollout strategies, creation checklists, and cleanup policies to prevent technical debt. Ideal for standardizing feature flag practices and governance.

This skill guides the creation of comprehensive Product Requirements Documents (PRDs) following industry best practices. It ensures all critical sections are included, such as problem statements, user stories, functional/non-functional requirements, technical considerations, and success metrics. Use it when formalizing a new feature or product specification for engineers and stakeholders.

This skill generates a comprehensive technical debt register for any team or service. It guides users to input critical data points (e.g., business impact, effort, tech stack) and produces a structured report that categorizes debt (Architecture, Security, Testing, etc.). The output includes a calculated priority score and a quarterly debt reduction roadmap, enabling deliberate, business-aware engineering decision-making.

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.

A comprehensive guide detailing the aesthetic and technical implementation of AI-native user interfaces for web and mobile applications. It emphasizes conversational flow, adaptive layouts, and generative state visual cues, providing CSS, SwiftUI, and Flutter code examples.