Skill UI

This skill serves as a senior QA automation architect to migrate and convert UI test automation scripts between popular frameworks, including Selenium, Playwright, Puppeteer, and Cypress. It handles complex conversions by applying API mapping, lifecycle adjustments, and pattern standardization, allowing users to port tests from one framework to another efficiently.

This skill helps generate comprehensive and structured TestNG test cases for Java. It supports advanced testing features crucial for enterprise automation, including method grouping, data-driven testing using @DataProvider, parallel execution setup, XML suite configuration, and custom listeners. Use it when building robust, scalable, and maintainable automated test suites.

A comprehensive guide for training or fine-tuning advanced sentence-transformer models. This skill assists in selecting the correct architecture—including Bi-encoders (SentenceTransformer), CrossEncoders (for reranking), and SparseEncoders—for various Natural Language Processing (NLP) tasks. Use cases include semantic retrieval, similarity matching, document clustering, and pair-wise classification.

This skill provides expert capabilities for training and fine-tuning transformer language models using the TRL (Transformers Reinforcement Learning) library. It supports state-of-the-art post-training methods, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), Group Relative Policy Optimization (GRPO), and Reward Model training. Use this skill to align and customize foundation models for advanced tasks via CLI commands.

This agent analyzes a Monte Carlo monitor's report and configuration to identify alert patterns. It recommends concrete configuration changes for metric, custom SQL, validation, and table monitors, helping reduce false positives and alert fatigue without sacrificing real signal.

A fast, grep-based linter that checks for common design system violations in CSS and component code, such as hardcoded colors, raw pixel values, and deprecated syntax. It provides immediate automated feedback to ensure code adheres to established design tokens and best practices.

A comprehensive guide and tool for applying sophisticated motion effects to UI components. Use it to select from five personality seeds (Spring, Silk, Snap, Float, Pulse) or specific descriptive keywords (like toggle-flip or shimmer). Ideal for defining the 'vibe' and functional transitions of any element in a modern user interface.

This skill provides a quantified design audit (0-100) for UI files based on StyleSeed's comprehensive design language. It breaks down the score into weighted categories (Color, Typography, Layout, etc.), identifies specific design violations, and generates a prioritized list of fixes, acting as a critical quality gate before deployment.

This meta-skill acts as a routing layer for complex UI development tasks. It guides the process of selecting the smallest, most specific, and useful skill context using the ui-skills CLI. Use it when starting UI work to analyze goals, identify the correct category, and pinpoint the precise skill set needed for implementation, ensuring development efficiency and accuracy.

This skill analyzes your project's current StyleSeed setup, detects outdated engine files, and safely updates the core components, skills, and rules. It follows a structured, non-destructive process, ensuring that user-defined code, such as theme.css and custom components, remains untouched while applying necessary upgrades.

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.