Skill UI

This skill guides users to create new Power Pages code sites (SPA) from scratch or using templates. It supports React, Angular, Vue, and Astro frameworks. The process covers requirements discovery, component planning, design, implementation, validation, and deployment. It ensures production-quality sites with live preview feedback loops and proper Git checkpoints.

This skill processes raw, report-only optimization observations generated by Caveman tools. It guides the user through an evidence-first, rigorous evaluation process, requiring explicit operator choice, designing a minimal candidate change, and performing a paired baseline evaluation using identical fixed inputs. It ensures that any proposed code change is validated against quality checks and established performance metrics before implementation.

This skill verifies completed work against acceptance criteria using a three-stage pipeline. It performs mechanical checks like linting and testing, semantic reviews for compliance, and multi-model consensus when uncertain. It supports automated fix loops and ensures code quality beyond simple test passing, providing proof of completion.

This skill systematically audits Playwright End-to-End (E2E) test files. It checks for common anti-patterns, adherence to best practices, and identifies coverage gaps across the entire test suite. It provides a detailed score (1-10) and generates actionable reports, including suggested code fixes, significantly improving test reliability and maintainability.

This skill generates high-quality, styled code screenshots by calling the ray.tinte.dev API. It allows users to convert raw code snippets into professional PNG images, supporting multiple programming languages (e.g., Python, JavaScript, TypeScript), customizable themes, and various styling parameters like font size and padding. Use this when the user explicitly requests code images, code snippets as pictures, or mentions 'ray' to visualize code.

skill-doctor grades the performance and quality of an AI agent setup using real, local conversation history (e.g., Claude Code/Codex sessions). It scores skills against defined rubrics for efficiency and code quality, drafts evidence-backed suggestions for improvement, and generates a comprehensive, shareable local report. All processing is strictly local and private.

Automates the conversion of visual designs from Stitch into high-quality, modular React and Vite components. This skill ensures strict adherence to modern architectural standards, including logic isolation via custom hooks, data decoupling, and robust type safety using TypeScript. It manages complex workflows like network fetching, style guide synchronization, and multi-phase validation to generate production-ready frontend code.

This skill analyzes excessively large Pull Requests (PRs) that exceed established line budgets (e.g., 400 lines). It automatically splits these massive changes into smaller, focused, and sequential PRs using advanced chaining or stacking strategies. This process is crucial for protecting reviewer focus, ensuring reviews can be completed within a manageable time budget (e.g., ≤ 60 minutes), and maintaining high code quality during complex feature integration.

Apply Robert C. Martin-inspired clean code rules to improve code readability, naming conventions, function design, and responsibilities. This skill ensures everyday implementation quality, readable control flow, and testable code by following established best practices for software development.

This skill applies Steve McConnell's construction rules to software development tasks. It covers routine design, variable usage, class design, control flow, defensive programming, coding standards, and testing. Use it for disciplined software construction to ensure high-quality code implementation.

This skill extracts a checklist from planned work, builds the implementation, and verifies every check with an independent verifier. It is used when the user requests to extract a checklist, build a ticket, or implement a spec. It ensures rigorous testing and proof-based assertions, preventing self-reporting of completion. It involves extracting checks, building the code, and proving each one independently to guarantee quality.

This skill verifies an MCP server before release by exercising a real protocol session. It compares runtime capabilities with source code and documentation, tests failure paths, and records reproducible evidence. Use this when shipping or reviewing an MCP server, tool, resource, prompt, catalog, or install path to ensure protocol behavior and transport correctness.