Skill UI

A comprehensive technical guide for implementing the nostalgic Frutiger Aero aesthetic across web and mobile platforms. This style, popular in the mid-2000s, is characterized by glossy gradients, translucent glass effects, and nature-inspired motifs (sky, water, grass), creating an optimistic, skeuomorphic user interface experience.

This guide details the principles and technical implementation of widget-based user interfaces, mimicking the aesthetic of modern mobile operating systems (like iOS Home Screen). It covers core design principles such as strict aspect ratios, glanceability, and corner radius matching. Practical code examples are provided for Web (CSS Grid), iOS (SwiftUI), and Cross-platform (Flutter) development, enabling designers to create modular, highly functional mini-apps.

An adversarial Quality Assurance (QA) pass designed to deep-dive into any codebase for logic errors, security flaws, and functional bugs. Instead of confirming that code 'looks right,' this skill actively attempts to break the code by simulating hostile inputs, tracing critical data paths, and checking for subtle, real-world correctness issues. Essential for high-stakes, critical code reviews.

A comprehensive skill for systematically building, refining, and documenting a project's domain model. It helps define core terminology, establish a ubiquitous language, and record critical architectural decisions (ADRs). Use this when you need to challenge ambiguous language, invent edge-case scenarios, or maintain architectural consistency throughout the development lifecycle.

This guide details the process of adding, verifying, and publishing necessary DNS records (SPF, DKIM, DMARC) for a custom sending domain in Mailtrap. It covers both manual compliance steps via the UI and programmatic automation through the Sending Domains API. Essential for ensuring high email deliverability and authentication compliance.

Use Mailtrap Email Sandbox to capture and inspect outbound emails without sending them to real recipients. This is crucial for development, staging, and CI/CD environments. It allows developers to test email content, headers, attachments, and spam scores using dedicated APIs, SMTP settings, or SDKs, ensuring mail integrity before deployment. Ideal for automation and rigorous quality checks.

This workflow helps developers quickly build throwaway prototypes to answer specific design or functionality questions. It can generate interactive terminal applications to test complex state/business logic, or create multiple radically different UI variations toggleable from a single view, allowing for rapid validation of ideas before committing to production code.

This skill scaffolds the necessary configurations for advanced engineering workflows. It guides the user through setting up the issue tracking system (GitHub, GitLab, or local markdown), defining the canonical triage label vocabulary, and establishing the domain documentation context (single or multi-context). It must be run once to initialize the repository for subsequent agent-driven development skills.

This tool evaluates how thoroughly a feature implementation meets product requirements (PRDs) or specifications. It scores acceptance criteria case-by-case, independently grading both the code implementation and the associated test coverage (unit and E2E). Ideal for benchmarking multiple development efforts, auditing adherence to specifications, or determining if a feature is 100% complete and compliant with the ground truth PRD.

This skill generates comprehensive, academic-style survey papers as a single, self-contained HTML file. By reading an anchor resource and curating research data, it structures the content and utilizes advanced LLMs (like Kimi K2.6 via Fireworks) to generate all prose, figures, and bibliographies, suitable for rapid academic literature review.

This skill guides the systematic triage of project issues and external pull requests (PRs). It moves development items through a defined state machine using roles (e.g., bug, enhancement) and states (e.g., ready-for-agent, wontfix). The process involves context gathering, cross-codebase verification, deep questioning (grilling), and generating comprehensive, agent-ready briefs or marking them for human implementation.

This document provides a comprehensive guide to the principles and vocabulary needed to write high-quality, predictable, and effective skills. It covers advanced concepts like model-invoked vs. user-invoked skills, managing context load, structuring information hierarchies (steps vs. reference), and implementing progressive disclosure to improve agent predictability.