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概要と使いどころ
Use when an idea becomes a Pixar-style animation prompt — character sheet, scene, image, video; emotional beat, want, obstacle. Triggers 'Pixar prompt', 'animated scene'. Live-action → video-director.
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。
[Design] Create or describe a UI design — quick (fast), immersive (good), or recreated/described from a screenshot or video, in a product-UI or marketing/creative lane. Dispatch via --mode={fast|good|describe|screenshot|video} (default fast) and --lane={product|marketing} (default product).
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。
Validate Commodore 64 VIC-II emulation in EMULATORS, including $D000-$D3FF register behavior, PAL/NTSC timing, raster counters, badlines, BA/AEC bus stealing, video matrix and bitmap fetches, sprites, collisions, borders, IRQs, color RAM usage, and display modes. Use when Codex reviews or edits VICII, Screen, Memory/PLA, raster, sprite, video, or cycle-level behavior for C64 classes.
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。
吉里吉里Z (kirikiri Z) 本体クラス API のリファレンス。TJS2 で吉里吉里Z 上のスクリプトを書く、レビューする、デバッグするときに使う。Layer / Window / Bitmap / System / Storages / Font / Plugins / Timer / Debug / AsyncTrigger / Scripts / BinaryStream / Matrix32 / Matrix44 / Rect / ImageFunction のコア API、サウンド系 (WaveSoundBuffer / SoundBuffer / VideoOverlay)、DrawDevice (BasicDrawDevice / SDLDrawDevice / OGLDrawDevice / GPUDrawDevice / NullDrawDevice)、OpenGL 描画系 (Canvas / Texture / ShaderProgram / Offscreen / VertexBinder / VertexBuffer)、および主要プラグイン提供クラス (HttpRequest / GdiPlus.* / WIN32Dialog / CSVParser / LineParser / Process / Pad / MenuItem / Unzip / Zip / PSD / SimpleHTTPServer) を網羅。**呼び出されたら必ず「共通パターン」と「クロスカッティング概念」を確認し、必要な詳細クラスは doc/reference/*.md を Read しに行くこと。** TJS2 言語そのものや組み込みクラス (Array / Dictionary / Math 等) は別 skill (`tjs2`) を参照。エンジン内部構造 (C++ 実装、レンダリングパイプライン詳細) は対象外。
Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video. Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video analysis", "audio transcription".
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。
Run 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search...
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Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, market...
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。
Extract frames or short clips from videos using ffmpeg.
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。
FFmpegを使用したマルチメディア処理の専門スキル。動画・音声の変換、編集、最適化を効率的に支援。フォーマット変換、コーデック選択、フィルタ適用、ストリーミング準備、ハードウェアアクセラレーションなど幅広い操作をカバー。Use when converting video/audio formats, transcoding codecs, trimming/cutting media, creating GIFs, extracting audio, adding watermarks, preparing for streaming (HLS/DASH), or optimizing media files for web/mobile.
Load Remotion best practices for React video creation, including animations, composition setup, assets, audio, captions, sequencing, transitions, media metadata, Three.js, Tailwind, and rendering patterns. Use when creating, editing, debugging, or reviewing Remotion code.
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。
Komponiert video-synchronisierte Hintergrundmusik aus einem Storyline-JSON per lokaler Waveform-Synthese (numpy + ffmpeg). Stile: Chiptune, Ambient, Electronic. Deterministisch, offline, kein Cloud-Dienst.
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。
Best practices for Remotion - Video creation in React
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- Verify whether an image or video is authentic, original and correctly captioned — provenance checks, error level analysis, noise and JPEG compression analysis, clone and copy-move detection, lighting and shadow consistency, C2PA… Use when fact-checking a photo or video, checking for a deepfake or AI-generated image, spotting manipulation, or testing whether footage is recycled or miscaptioned
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。
Create programmatic videos using React and Remotion. Translate natural language descriptions into working Remotion components for product demos, release announcements, explainer videos, and animated content.
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When the user wants to create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,' 'hero image,' 'social media graphic,' 'banner image,' 'cover photo,' 'profile banner,' 'listing screenshot,' 'Flux,' 'Flux Kontext,' 'Midjourney,' 'DALL-E,' 'GPT Image,' 'ChatGPT Images,' 'Ideogram,' 'Gemini image,' 'Nano Banana,' 'Recraft,' 'Stable Diffusion,' 'Canva,' 'Figma,' 'image optimization,' 'compress images,' 'WebP,' or 'OG image.' Use this for general-purpose marketing image creation and optimization. For paid ad image creative and platform-specific ad specs, see ad-creative. For video production, see video.
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 the user asks to "amplify influencer content with paid media", "set up whitelisting or Spark Ads", "decide which posts to boost", "repurpose influencer content", "turn one video into multiple ads", or "build a UGC asset library"; produces (paid mode) a content-selection scorecard, a paid amplification strategy (whitelisting/boosting/dark posts), audience targeting, and a budget+optimization plan, or (repurpose mode) a rights-tracked content inventory, a 1-video-to-10+-asset repurposing map, per-format transformation specs, and a 30-day distribution plan. Not for gating whether a deliverable is publishable or FTC-compliant — use creator-content-auditor; not for the always-on brand posting calendar — use social-calendar-builder; not for drafting a net-new idea into platform-native packages — use social-creative-builder. 复用达人内容 / 内容放量.
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。
Audit paid-ad copy, images, video, hooks, concepts, format coverage, platform-native fit, message match, creative fatigue, accessibility, and policy across supported platforms. Use for creative audit, ad creative, creative fatigue, creative diversity, ad copy review, video review, image review, or production priorities.
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。
Audit YouTube Ads campaign setup, video and Demand Gen inventory, Shorts, in-stream, CTV, creative, audiences, brand safety, bidding, and measurement. Use for YouTube Ads, video ads, pre-roll, bumper ads, skippable in-stream, Shorts ads, Demand Gen, VAC migration, CTV, or YouTube campaign optimization.
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。
Master orchestrator for B2B SaaS content creation and the editorial production system behind it. Use this skill to produce blog articles, whitepapers, case studies, video scripts, newsletters and ghostwritten thought leadership, to develop content strategy, and to run the publishing line itself — content briefs, editorial calendars and production capacity, review and approval workflow, subject-matter-expert access, the style guide, an AI-drafting policy, and a content inventory with owners. Also triggers on: blog, article, case study, whitepaper, newsletter, video script, ghostwriting, content calendar, editorial, thought leadership, content strategy, content brief, content operations, content ops, editorial workflow, managing editor, who reviews this, our content pipeline is stuck, content is stuck in review, content audit, content inventory, content governance, style guide, house style, SME interview, expert interview, freelance writers, AI content policy, how much content can we actually produce.
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。
Translate creative intent into coherent cinematography, framing, camera, lens, lighting, motion, and sound direction for a video shot.
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。
Turn an authorized long-form video into a ranked set of YouTube Shorts candidates with vertical framing, captions, timestamps, and source provenance.
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。
Plan draft video-ad variations from supplied performance evidence, preserving the distinction between observed data and creative hypotheses.
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。
Create a non-explicit romantic scene from authorized adult references with clear consent, identity boundaries, and synthetic-media labeling.
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。
Create authorized presenter, avatar, and UGC-style video drafts with explicit voice, likeness, consent, and synthetic-media handling.
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。