「scene selection」の検索結果

Create Viking web projects, start and verify a local preview, or deploy a generated project to Volcengine IGA Pages when explicitly requested. Includes agent-guided feature, eligible application, dataset, scene, and authentication choices. Use only after confirming the installed CLI exposes `vs project`; otherwise stop without taking action.

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Use for AI-assisted Unity work that needs live repo discovery, project-derived routing, runtime-owner proof, runtime-visible output hard stops, runtime numeric proof for repeated visible-output failures, state-step guards, multi-agent scope ownership, modular C#/asmdef safety, UI/scene/visual asset gates, data-first content changes, validation, cleanup proof, or durable workflow rules. Best when agents must prove the actual folder/module/scene/prefab/runtime owner before editing, especially runtime UI, generated assets, code graphs, tutorial/state flows, guided selection/action flows, overlay/dim source-bound mistakes, coordinate conversions, focus/highlight/marker/HUD alignment, predictive lead aiming, ballistic trajectories, spatial IoU verification, or repeated "fix still not visible" failures.

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Generate AI images using Gemini or GPT APIs directly. Covers model selection (Gemini for scenes; GPT Image 2 for text rendering, batch variations, multi-reference compositing; GPT Image 1.5 for transparent icons), the 5-part prompting framework, API calling patterns, multi-turn editing, and quality assurance. Produces photorealistic scenes, icons, illustrations, OG images, posters, infographics, and product shots. Use when building websites that need images, creating marketing assets, or generating visual content. Triggers: 'generate image', 'ai image', 'create hero image', 'make an icon', 'generate illustration', 'create og image', 'poster', 'infographic', 'image variations', 'gpt-image-2', 'ai art', 'image generation'.

日本語の概要は準備中です。原文の説明を表示しています。

Build typed data visualizations in TypeScript. Use when the user wants TypeScript visualization code, typed data models, browser visualization components, UML-like diagram models, interactive graph or architecture diagram contracts, scroll-driven scene contracts, library selection guidance, or a maintainable visualization architecture beyond React- or Next-specific concerns.

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Premise, theme, controlling idea, subject selection and logline for scripts (前提/主题/立意/选材/戏核) — merged from Lajos Egri's premise-as-tyrant and dialectic, Robert McKee's controlling idea (value + cause) and idea/counter-idea, Neill Hicks' five premise questions, Lisa Cron's "third rail" (desire vs misbelief, origin scene, what-if), Julian Hoxter's logline and theme-attitude rule, Blake Snyder's logline/genre/title tests, and Lu Jun's Chinese craft chapters on 选材要严/开掘要深/视角要新/戏核要好/情节要奇. Use when turning a vague idea into a premise, finding what a story is really about, choosing a subject and angle, testing a logline, deciding the ending from the theme, or diagnosing a script that "has events but no story".

日本語の概要は準備中です。原文の説明を表示しています。

Use when designing a new Godot feature or system — guides scene tree planning, node type selection, and architectural decisions

日本語の概要は準備中です。原文の説明を表示しています。

Produce presenter-led AI avatar videos with Synthesia Studio and Synthesia API. Use for Synthesia-specific avatar video planning, avatar/voice/language selection, scripted scenes, template personalization, API job lifecycle, localization/dubbing, brand/training/product workflows, consent/rights/safety checks, artifact custody, troubleshooting, and final QA.

日本語の概要は準備中です。原文の説明を表示しています。

Produce HeyGen avatar videos with Direct Video, Video Agent, Digital Twin, Avatar Realtime, and related avatar/voice/asset APIs. Use for provider routing, avatar and voice selection, script-to-video workflows, lip-sync from audio, backgrounds/scenes, callbacks and polling, consent and rights checks, localization handoffs, artifact custody, QA, and troubleshooting HeyGen avatar-video productions.

日本語の概要は準備中です。原文の説明を表示しています。