Skill UI

This expert assistant specializes in creating, generating, editing, and optimizing professional visual assets for marketing campaigns. Whether you need blog heroes, social media graphics, product mockups, or brand banners, it guides you through selecting the right AI model (e.g., Gemini, Midjourney, Ideogram) or design workflow (e.g., Figma, Canva). It provides best practices for prompting, consistency, and web optimization, ensuring high-quality, brand-compliant visuals every time.

This elite skill acts as an art director and implementation strategist for modern web development. It mandates an 'Image-First' workflow: first generating high-fidelity, premium design images for specific sections (e.g., hero, product features), deeply analyzing these visual references, and only then translating them into clean, structured, and highly implementable frontend code. It is designed to avoid generic AI clichés, ensuring results that are aesthetically superior, structurally sound, and ready for professional deployment.

An elite skill dedicated to generating premium, app-native, and highly readable UI/UX concept images. It visualizes entire application flows—from onboarding and authentication to complex dashboards—for iOS, Android, and cross-platform products. The focus is on creating believable, highly intentional designs with strong consistency, controlled color palettes, and clean hierarchies, avoiding generic, default-style mockups.

This skill acts as an elite art director, generating highly structured, premium, and conversion-aware frontend design references. It is optimized for creating multi-section websites, landing pages, and marketing sites, ensuring consistency and visual appeal across every section. Output is designed to be immediately usable by developers or coding models, adhering to strict composition rules to avoid generic AI aesthetics.

This structured skill guides users through root-cause-first debugging when an implementer is blocked, verification fails, or repeated attempts at fixing do not converge. It mandates a systematic approach combining local evidence inspection, runtime analysis, and external documentation research to accurately classify the failure's true source (e.g., missing dependency, spec conflict). It prevents speculative patching and generates a clear, actionable fix plan.

This tool systematically converts a project roadmap into actionable specifications. It first analyzes features by grouping them into dependency waves. It then automatically dispatches sub-agents to generate complete feature specs (requirements, design, tasks, and JSON) for each wave. The core value lies in its comprehensive cross-spec review, which verifies data model consistency, interface alignment, and architectural integrity across the entire project, ensuring a cohesive final product.

This skill helps users create specialized 'steering documents' or project memory for highly specific domains (e.g., API standards, testing strategies, security patterns). By analyzing the existing codebase and following predefined architectural principles, it synthesizes concise, actionable guides that capture technical patterns, best practices, and domain-specific rules, ensuring project consistency and knowledge retention.

This comprehensive skill guides users through the entire Fluid storage extension lifecycle within KubeSphere. It allows for installing, upgrading, and uninstalling the Fluid extension, and managing various data resources. Users can generate YAML manifests for Datasets and specialized runtimes (Alluxio, JuiceFS, Thin), perform data loading/cache warming, scale operations, and troubleshoot issues using both kubectl and KubeSphere APIs.

A comprehensive guide for managing the full lifecycle of OpenKruise within the KubeSphere platform. This skill assists users with installation, upgrading, querying status (CRDs, Pods, logs), generating manifests for advanced workloads (SidecarSet, CloneSet), performing rollouts, and troubleshooting complex runtime issues like webhooks or missing configurations, utilizing both kubectl and KubeSphere APIs.

A comprehensive skill for managing the entire lifecycle of Volcano Jobs within the KubeSphere environment. It supports the scheduling and execution of complex batch workloads, including deep learning tasks using PyTorch and TensorFlow, MPI, and general resource-intensive jobs. Provides detailed API usage and troubleshooting guidance for job scheduling and resource conflicts.

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.

Master the complexities of building robust Retrieval Augmented Generation (RAG) pipelines using LangChain. This guide addresses common pitfalls in vector search, such as score semantics differences (L2 vs. Cosine), embedding dimension mismatches, and chunking issues for code/Markdown. Learn best practices for selecting between FAISS, Pinecone, Chroma, and PGVector, normalizing scores, and implementing hybrid keyword+vector search for maximum retrieval quality.