productivity▌

Professional image generation with advanced text rendering, photorealistic details, and semantic accuracy via Alibaba Qwen-Image-2.0-Pro. \n \n Excels at text-heavy designs including posters, banners, and multi-line text with fine-grained control over font, color, and positioning \n Generates 1–6 images per request with configurable dimensions (512–2048 pixels), negative prompts, and reproducible seeds \n Supports image editing and style transfer via reference images for outfit swaps and creativ

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Strategically introduce color to monochromatic designs while maintaining hierarchy, accessibility, and visual restraint. \n \n Requires running the frontend-design skill first to establish design context and gather existing brand colors \n Guides systematic color application across semantic states (success, error, warning, info), accents, backgrounds, data visualization, borders, and typography \n Enforces a 60-30-10 color distribution rule and WCAG contrast compliance to prevent overwhelming or

Simple-earn request on Binance using authenticated API endpoints. Requires API key and secret key for certain endpoints. Return the result in JSON format.

Run QLTY checks during code writing to catch issues early.

Enforce verification commands before claiming work completion, fixes, or test passes—no success assertions without fresh evidence. \n \n Requires running the actual verification command (not assumptions or partial checks) and confirming output before making any completion or correctness claims \n Applies to all success-related statements: test passes, builds succeeding, bugs fixed, requirements met, regressions verified, and agent task completion \n Blocks common shortcuts like trusting agent re

Generate a concise, professional equity research earnings preview for a single company. The output is a self-contained HTML file targeting 4-5 printed pages. The report is dense with figures and data, with tight narrative that gets straight to the point.

Identify and extract reusable components, design tokens, and patterns into a cohesive design system. \n \n Analyzes target areas to find repeated UI patterns, hard-coded values, and inconsistent variations worth systematizing \n Guides extraction planning including component APIs, token hierarchies, naming conventions, and migration strategies \n Emphasizes incremental growth: extract only patterns used 3+ times or with clear reuse potential, avoiding over-generalization \n Includes accessibilit

The recommended way to load textures in R3F.

Rethink designs for different screens, devices, and contexts while maintaining consistency. \n \n Assess source and target contexts (device type, input method, screen size, connection speed, usage patterns) to identify what won't fit or work across platforms \n Apply context-specific strategies: single-column layouts and touch targets for mobile, two-column hybrid layouts for tablet, multi-column and hover states for desktop, narrow widths and inline CSS for email \n Use responsive techniques in