Skill UI

This skill automatically rewrites raw commit messages to adhere to professional engineering standards. It strips out common 'AI/marketing slop' phrases (like 'robust implementation' or 'leverage') while strictly maintaining the Conventional Commits format. It ensures subjects are concise, bodies provide necessary context (why, breaking changes), and the tone is direct and actionable, making your project history clean and readable.

Specialized skill to rewrite and humanize AI-generated natural language files (like notes or documentation). It removes common 'AI-isms' such as sycophantic openings, stock vocabulary, over-explaining, and excessive signposting. Users can choose between a fast, deterministic regex cleanup or a deep LLM rewrite (default mode) using Claude to enhance burstiness and match a natural human voice, all while strictly preserving code blocks, URLs, and headings.

Rewrites overly formal or vague code review comments generated by AI or corporate tools. It cuts out filler phrases like "I noticed..." or "It might be worth considering...", transforming them into direct, actionable feedback. The output uses a clear format (Location: Severity: Observation. Fix.) that sounds like it came from a helpful, experienced teammate, significantly improving the quality and reception of PR feedback.

This skill systematically scans Apple's comprehensive developer documentation, specifically targeting SwiftUI. It identifies deprecated APIs, finds their modern replacements, and updates the expert skill's reference guide. Use this when required to refresh deprecated features, check for new API deprecations after an iOS/Xcode update, or maintain the most current best practices for SwiftUI development.

A comprehensive guide to designing transparent, predictable, and developer-friendly usage-based pricing models. Learn which metrics (API calls, compute time, storage) developers accept, how to structure clear pricing pages, and how to avoid confusing or punitive billing practices to maximize adoption and revenue.

Utilizes Expo DOM components to render web code verbatim inside a webview on native platforms, while maintaining native rendering on the web. This enables developers to integrate web-only libraries (such as charting tools, syntax highlighters, or complex CSS layouts) and incrementally migrate existing web components into a React Native application without substantial rewriting.

This skill generates comprehensive end-to-end (E2E) automation tests using WebdriverIO (WDIO) in JavaScript or TypeScript. It supports various frameworks (Mocha, Jasmine, Cucumber) and includes advanced patterns like the Page Object Model (POM) and robust selector strategies. Users can configure tests for local execution or integrate with cloud services like LambdaTest, making it ideal for simulating complex user interactions and ensuring application quality across multiple browsers and environments.

Generates championship-grade, F1-inspired test suites based on the WJTTC methodology. This skill enforces a 'tests first' philosophy, analyzing the codebase to define structured test plans. It covers standard industry unit tests (Layer 1) and deep expert edge cases (Layer 2). Furthermore, it includes Signal Integrity Audits to ensure the test suite's reliability is paramount, guiding development toward maximum code quality.

This skill applies rigorous, F1-inspired standards to software quality assurance. It executes comprehensive test plans, classifies failures across five critical tiers (Brake, Engine, Aero, Tyre, Pit), audits Continuous Integration (CI) signal integrity, and generates detailed WJTTC reports. Use it to validate functionality, reproduce complex bugs, or determine the readiness of a release.

This skill enforces a rigorous, multi-phase coding workflow (Discuss -> Map -> Decompose -> Execute -> Verify) to ensure code is structurally grounded, complete, and free from invented APIs or assumptions. It is designed for high-stakes, complex, or multi-file engineering tasks, acting as a senior, disciplined coding partner that plans meticulously before writing code.

Before You Build acts as a crucial checkpoint in the AI coding workflow. It prevents premature implementation by rigorously assessing product risk—analyzing market demand, existing user workflows, switching costs, and distribution channels. Instead of writing code, it guides the user to define core assumptions and propose the smallest, most effective validation test (e.g., landing page test, user interview) before committing resources.

A powerful plugin enabling Claude Code to delegate complex tasks to external AI CLIs (such as OpenAI Codex or Google Antigravity/Gemini) without exiting the conversation. It supports multi-model workflows, allowing users to seek a second opinion, cross-check deep analysis, or delegate side tasks (like research or code review). The core value is that Claude synthesizes the raw outputs, providing a critical review and reconciliation of findings across all consulted models.