242건 · 관련도순
Comprehensive GLSL shader techniques for creating stunning visual effects — ray marching, SDF modeling, fluid simulation, particle systems, procedural generation, lighting, post-processing, and more.
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Augmented reality (AR) reality tech. Passthrough overlays, hit-test/anchors, occlusion, lighting, camera permissions, and safety.
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Maximum control over AI image generation — write structured VGL (Visual Generation Language) JSON that explicitly controls every visual attribute. Define exact object placement, lighting direction, camera angle, lens focal length, composition, color scheme, and artistic style as deterministic JSON instead of ambiguous natural language. Use this skill when you need reproducible image generation, precise control over scene composition, or want to convert a natural language image request into a structured JSON schema for Bria Fibo models. Triggers on requests for structured prompts, controllable generation, VGL JSON, deterministic image descriptions, or Bria/FIBO structured_prompt format.
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Vehicle/automotive image editing for cars, trucks, SUVs, motorcycles — car scenes, reflections, tires refinement with snow/mud/grass, segment windshield/wheels/body/windows/hubcaps, atmospheric effects (dust, fog, snow, light leaks, lens flare), and lighting harmonization (hot-day, cold-day, hot-night, cold-night presets). Powered by Bria.ai's dedicated automotive pipeline. Use this skill whenever the user mentions a car, vehicle, truck, SUV, motorcycle, auto photo, car reflections, tire enhancement, muddy tires, vehicle background, automotive marketing, car dealership visual, vehicle configurator, or car scene generation. ALWAYS prefer this skill over general image tools when the subject is a vehicle — faster and more accurate for automotive workflows.
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Director-level AI art prompt creation for Eastern beauty series, including Eastern fantasy / gu feng Chinese beauty character art, classical Eastern beauty, realistic and modern Eastern beauty, Cosplay展会摄影 / official convention cosplay photography with AAA game character campaign and Vogue editorial quality, 古风闺蜜 / AncientFemaleCompanionship two-person ancient Chinese female companionship photography, 东方美学图鉴 / 小红书图鉴 cover and content systems for 四大美人、四大才女、十二花神、东方神女、敦煌飞天、朝代服饰、东方器物、东方神话, 甜系纯欲生活写真 / SweetHomeGirl lifestyle portraits built around realism, feminine charm, romantic feeling, story moment, and natural attraction, new-Chinese-style fashion editorials, magazine portraits, worldbuilding, mythic role design, costume/styling systems, cinematic composition, lighting, negative prompts, and model-specific prompt variants. Use when the user asks for 东方美人, 东方审美, 东方美学图鉴, 小红书图鉴, 图鉴封面, 图鉴正文, 四大美人, 四大才女, 十二花神, 东方神女, 敦煌飞天, 朝代服饰, 东方器物, 东方神话, Cosplay展会摄影, coser, Coser, 漫展摄影, 展会摄影, ChinaJoy, Bilibili World, Tokyo Game Show, 游戏展台, 官方展会摄影, AAA游戏角色Cosplay, 古风闺蜜, AncientFemaleCompanionship, Ancient Female Companionship, 闺阁夜话, 姐妹古风写真, 古代闺阁生活, 灯下梳发, 共读, 夏夜纳凉, 守夜, 江南同行, 湖亭共伞, 山寺同行, 灯会夜游, 柔美, 妩媚, 成熟, 优雅, 高贵, 清冷, 温婉, 英气, 神性, 慵懒, 东方幻想, 古风美女, 古典东方美人, 宋韵, 唐宫, 江南, 洛神, 青瓷, 昆曲, 国风人物, 汉服女子, 写实东方美人, 现代东方审美, 新中式, 东方高级感, SweetHomeGirl, 甜系纯欲生活写真, 甜系纯欲, 甜美女友感, 真实女生, 自然抓拍, 故事感, 女友视角, lifestyle girlfriend portrait, 仙侠/武侠/宫廷/江南/敦煌风 AI 绘画提示词, image prompt optimization, style word expansion, character series concepts, or prompt packs for Midjourney, Stable Diffusion, ComfyUI, DALL-E, Gemini, Seedream, or other image generation tools.
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Food photography audit — reviews existing photos, identifies missing item photos, provides specific shot list with angles, lighting, and styling direction
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Build a persistent visual brand identity for image generation. Defines how the brand looks visually — aesthetic, lighting, composition, mood — and writes it to brand/creative-kit.md so /image-gen and other creative skills produce consistent on-brand visuals. Three modes: Extract (from website/URL), Build (interview), Reference (mood board/examples). Use when starting any project that needs images, when the user says "visual style", "brand aesthetic", "image style", "visual identity", "how should our images look", "build visual brand", "define our look", or when /image-gen outputs feel generic because no visual style exists yet.
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Create 3D web experiences: scene setup, models, materials, lighting, animation, scroll-driven scenes, and performance budgets. Use when adding 3D to websites beyond basic demos.
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Create 3D visuals with modeling, texturing, lighting, rendering, and optimization for web and product.
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Use when a task needs the judgment of a Desktop Publisher — laying out a multi-page document on a grid system, applying typesetting rules (kerning, leading, widow/orphan control), preflighting a file for print (bleed, color mode, image resolution) before it goes to press, or deciding between a template and a custom layout under a deadline.
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Unity 6 2D game development guide. Use when building 2D games, working with sprites, sprite atlas, SpriteRenderer, tilemaps, 2D physics (Rigidbody2D, Collider2D), 2D lighting, sorting layers, or sorting groups. Based on Unity 6.3 LTS documentation.
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ออกแบบภายใน — functional layout, furniture spec, lighting plan, material palette, mood board พร้อม render prompt
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Photography expert for composition, lighting, camera settings, and post-processing techniques
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Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in HyperFrames HTML. Use when asked to build any HTML-based video content, add captions or subtitles synced to audio, generate text-to-speech narration, create audio-reactive animation (beat sync, glow, pulse driven by music), add animated text highlighting (marker sweeps, hand-drawn circles, burst lines, scribble, sketchout), or add transitions between scenes (crossfades, wipes, reveals, shader transitions). Covers composition authoring, timing, media, and the full video production workflow. For dev-loop CLI commands (init, lint, inspect, preview, render) see the hyperframes-cli skill; for asset preprocessing commands (tts, transcribe, remove-background) see the hyperframes-media skill.
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Generate advertising images automatically from a product URL + brand profile. ✅ USE WHEN: - User provides a product URL (e-commerce link) - Want automated product scraping + image generation - Have a brand profile to apply (70+ brands available) - Need funnel-stage targeting (awareness/consideration/conversion) - Want AI to auto-select model, scene, lighting based on brand ❌ DON'T USE WHEN: - User provides local product image file → use morpheus-fashion-design - Don't need a person in the image → use nano-banana-pro - Want manual control over model, scene, packs → use morpheus-fashion-design - Already have hero image, need variations → use multishot-ugc - Need video output → use veed-ugc after image generation INPUT: Product URL + brand name (optional) + funnel stage (optional) OUTPUT: PNG advertising image with product + model
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Romantic couple hugging on a beach at sunset, cinematic lighting, soft focus, using reference faces
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Multi-age family playing in a park, golden-hour lighting, candid expressions, using reference photos
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Epic fantasy group portrait in a magical forest, mystical lighting, dynamic poses, remove objects from original photo, using reference faces
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Three women posing in urban street fashion, dramatic lighting, stylish hairstyles, using reference faces
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Describe patterns that may indicate bad-faith or manipulative communication including gish gallop, whataboutism, tone policing, motte-and-bailey, sealioning, lying by omission, deflection, and strategic evasion. Use when the user suspects manipulation, notices repeated non-engagement, wants to analyze debate tactics, or mentions 'bad faith', 'deflection', 'manipulation', 'dodging the question', 'avoiding the issue', 'gaslighting', 'moving goalposts'. Describes behavioral patterns without making psychological diagnoses.
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Build UpSet plots to visualize set intersections beyond 4 sets (where Venn fails) using ComplexUpset (modern, ggplot2-grammar) or the unmaintained UpSetR, with explicit cardinality vs degree sorting, attribute panels, and query highlighting. Use when comparing overlap across many gene sets, peak sets, variant lists, or any set membership matrix where Venn diagrams become illegible.
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Generate realistic product-in-use lifestyle scenes. Places the product in believable contexts of use (who, where, when, doing what) with natural lighting and real texture, for lifestyle/editorial/ecommerce. Use when the user says "lifestyle shot", "product in use", "scene", "show it being used", "in-context photography", or needs people/environment around the product. Part of the Creative Production set.
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Reference for Starlight — the Astro documentation theme the gatOS docs site (under site/) is built with. Use this when authoring or editing tutorial/reference pages: which built-in component to reach for and its exact props (Aside, Tabs/TabItem, Steps, Card/CardGrid, LinkCard, LinkButton, FileTree, Badge, Icon, Code), the page frontmatter schema (title/description/sidebar/tableOfContents/…), the `:::` asides syntax, and the Expressive Code block meta-string (titles, line/text highlighting, diff markers). A self-contained cheat sheet so a session can build a polished page without the Starlight docs site. Pair with the `astro` skill (the framework under it) and `tutorials` (house style).
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Expert-level computer graphics covering the rendering pipeline, rasterization, ray tracing, shaders, transformations, lighting models, and GPU programming.
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