「motion」の検索結果

A heart/favorite icon that animates on toggle — Lottie JSON, portable across web & app. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.

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。

A floating action button that morphs open — Lottie JSON. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.

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。

An animated bottom-tab indicator — Lottie JSON. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.

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 a real website's design tokens — colors, typography, spacing, CSS, and motion — into a structured `design.md` an AI can consume. Use to seed motion-anything's design system from an existing site so generated motion stays on-brand ("扒这个网站的配色/字体", "design.md from url").

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。

Amazon deal planning and promotional strategy optimization. Lightning Deals, Best Deals, Coupons, Prime Exclusive Discounts analysis and ROI calculation. Deal eligibility assessment, timing optimization, and promotional campaign planning. Use when the user asks about Amazon deals, Lightning Deals, promotional planning, deal strategy, or Amazon promotions.

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。

Framer Motion / Motion sub-skill - AnimatePresence, layout animations, gestures, motion values.

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。

Still-to-video conversion guide: model selection, motion prompting, and camera movement. Covers Wan 2.5 i2v, Seedance, Fabric, Grok Video with when to use each. Use for: animating images, creating video from stills, adding motion, product animations. Triggers: image to video, i2v, animate image, still to video, add motion to image, image animation, photo to video, animate still, wan i2v, image2video, bring image to life, animate photo, motion from image

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。

Implement smooth, accessible animations with motion/react (Framer Motion) in React. Use when adding animations, gestures, or layout transitions with motion, AnimatePresence, useScroll, and related APIs. Requires a 'use client' boundary; not for strictly server-rendered components or when no animation is needed.

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。

Tasteful, subtle web UI animation following Emil Kowalski / animations.dev principles. Use when adding or reviewing interface motion — hover and press feedback, entrances and exits, modals, toasts, menus, loading and skeleton states, staggered reveals, page or view transitions — so motion stays refined and purposeful, not decorative. Covers CSS, Web Animations, and React timing/easing. Pair with the motion skill for motion/react API specifics.

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。

Define a product's motion design language -- duration and easing scales, choreography rules, and signature moves -- and export it as tokens plus ready-to-use Framer Motion variants and CSS. The difference between animations and a motion system: everything moves like it belongs to the same 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。

Guides DeepMotionEditing BVH animation, skeleton-aware motion retargeting, motion style transfer, and Blender visualization workflows for research use.

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。

Learn reusable 2D motion-generation knowledge from user-specified action resources with `/img2mo-learn <resource>`. Use when the user provides videos, extracted frame sequences, spritesheets, Spine assets, generated outputs, failed attempts, or reference motion folders and wants to summarize animation timing, pose beats, style traits, prompt patterns, extraction/cropping rules, or failure lessons into the project `img2mo-knowledge/` folder for later `/img2motion` 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。

Legacy v1 (voiceover-led, GSAP + HyperFrames). Use when making, directing or rescuing a product launch video, promo, teaser, demo reel, sizzle, feature-announcement film or animated product explainer built from code — and when an existing one looks basic, reads as a slideshow, has reveals that miss the voiceover, an invisible cursor, an inaudible sound effect, a clipped or too-quiet mix, or every video coming out looking the same. Covers SaaS, apps, hardware, e-commerce, dev tools, services. Keywords include motion design, storyboard, voiceover sync, kinetic typography, GSAP, HyperFrames, Remotion, film grain, LUFS, 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。

Use when asked to make a launch video, product film, motion design piece, UI motion reel, Dribbble-style UI animation or animated brand/logo sting — anything rendered to MP4 from HTML with a cursor, morphing UI, springs, beat-synced music and SFX. Carries Chan's full creative direction (one shape never cut, blur content swaps, springs, real data, logo slams, no creative limits) and the proven build/render pipeline (pure seek(t), closed-form springs, Playwright subframes, ffmpeg tmix, numpy beat grid).

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

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 wants to design, rewrite, refine, or vary emotional acting prompts for live-action AI video characters. Translate abstract emotions, dialogue, subtext, and scene context into concise, observable, temporally ordered micro-performance directions. Preserve the user's existing character, scene, camera, and dialogue requirements unless they explicitly ask to change them. Do not use for general story writing, shot design, action choreography, or visual asset design when emotional performance is not the main task.

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。

All animation knowledge for HyperFrames — atomic motion rules, multi-phase scene blueprints, scene transitions, broader motion-design techniques, AND the seven runtime adapters (GSAP default, plus Lottie, Three.js, Anime.js, CSS keyframes, Web Animations API, TypeGPU). Use for any motion or animation task: pick 2-4 rules and compose, or load a blueprint, or look up runtime-specific API (e.g. GSAP eases / Lottie player / Three.js mixer). HyperFrames-native: single paused timeline, seek-safe, deterministic.

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。

Expert in real-time game animation systems including skeletal animation, blend trees, state machines, inverse kinematics, root motion, procedural animation, and animation retargeting. Specializes in creating fluid, responsive character animation that balances visual quality with performance constraints. Use when "animation system, state machine, blend tree, skeletal animation, inverse kinematics, IK system, root motion, animation blending, character animation, animator controller, motion matching, animation retargeting, foot IK, look at IK, aim offset, animation montage, animation notify, additive animation, animation layers, procedural animation, animation, game-dev, character, state-machine, unity, unreal, godot, skeletal, rigging, motion" mentioned.

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。

This skill should be used when the user asks to "make a video with Remotion", "create a programmatic/data-driven video in React", "render an MP4/GIF from code", "animate with useCurrentFrame/interpolate/spring", "sync video to audio/beats", or "render a templated video per record headlessly". Covers building React compositions and rendering them via CLI or @remotion/renderer.

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。

This skill should be used when the user asks to "make this animation feel natural", "fix motion that feels stiff/floaty/cheap", "my animation looks robotic", "choose an easing curve", "how do I use the Graph Editor", "add overshoot or bounce", "Easy Ease isn't enough", "make snappy motion", "pick a duration for this transition", "stagger a list animation", "sync animation to a beat", or "review motion for good timing". It is the tech-agnostic foundation for deciding how something should move.

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 GPU-accelerated animations with Web Animations API (WAAPI), Scroll-Driven Animations (ScrollTimeline/ViewTimeline), FLIP technique, easing systems, and accessibility (prefers-reduced-motion). Use when user asks to create animations, transitions, scroll effects, page transitions, or interactive motion for web UIs. Do NOT use for canvas-based animations (Three.js, PixiJS), video editing, or non-web (native mobile) motion design.

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 and debug SceneKit scenes where one 3D object (a product, badge, coin, wheel) performs on a transparent stage inside a SwiftUI app - studio lighting, real shadows, baked keyframe choreography, hand-rolled physics, gestures and haptics, multi-scene sequencing. Use when working with SCNView or SceneView in SwiftUI, UIViewRepresentable 3D scenes, product or hero-object animation, roll or spin entrances, a first-frame hitch when a scene appears, shadows missing or wrong, metal rendering black, choreographed 3D motion that must stay interruptible, a continuous vapor stream (vent air, steam, mist) drawn as a shader-driven sheet, a liquid-metal or jelly blob (noise-deformed surface with mirror reflections and tap ripples), chrome or gold that looks cartoon-flat instead of real, HDRI image-based lighting, free trackball rotation of an actor, deterministic screenshot testing of shader-driven scenes, cutting an actor in two with a finger swipe (runtime mesh slicing with sealed cross-sections and a falling piece), a die-struck relief object (badge, coin, medallion) built from a heightfield with multiple finishes on one mesh, an actor crumbling into debris that falls and rests on the floor, reproducing a real object's motion from photos or video, or keyframed motion that stutters at its own keyframes. Not for RealityKit, ARKit, visionOS, or full game worlds.

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。

Lightweight, script-driven variant of data2motion for turning data into a smooth, on-brand animated chart (one self-contained HTML) — built for a TEXT-ONLY model that cannot see its own output. You never write HTML/CSS/SVG/animation; you extract the data, pick a chart, fill a small JSON spec, and run one build script that owns 100% of the look and the motion, so the result cannot drift from the house template style or lose its smoothness. Use to turn a number/stat/table/CSV/paragraph into a quick animated chart, data reveal, or KPI when you want guaranteed template fidelity with minimal reasoning and no image feedback.

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。

🇺🇸 Reddit Marketing & Growth Playbook 2026 — The complete Reddit operations SOP for AI/SaaS founders. Covers account warming (Karma 0→500 in 20 days), shadow ban prevention, multi-account matrix via fingerprint browsers, subreddit selection across 10K+ communities, content templates (90/10 rule), Product Hunt × Reddit flywheel, AMA strategy. Why this matters NOW: Reddit content is 40.11% of ChatGPT/Claude training data — the highest-weighted English UGC source. Battle-tested by AFFiNE Reddit campaigns generating 3-4万有效曝光 with 5-8% GitHub Star conversion, plus 7 case studies (Adobe 3x conversion, Base44 $80M AMA, SenseNova-U1 multi-sub launch, Starterstory 0→3K users). 🇨🇳 Reddit 运营增长实战手册 — AI/SaaS 出海 founder 的 Reddit 完整 SOP。覆盖账号体系(20天养号 Karma 0→500)、影子封禁防御、指纹浏览器矩阵、10万+ subreddits 筛选、内容模板(90/10 法则)、Product Hunt × Reddit 飞轮、AMA 打法。**为什么现在做:Reddit 内容占 ChatGPT/Claude 训练数据 40.11%,是最高权重的英文 UGC 来源**。基于 AFFiNE Reddit 实战 3-4 万曝光 + 5-8% Star 转化,含 7 个完整案例(Adobe 3x 转化、Base44 $80M AMA、SenseNova-U1 多社区联动、Starterstory 0→3K 用户冷启动)。 🇯🇵 Reddit マーケティング＆グロースプレイブック — AI/SaaS創業者向けの完全なReddit運用SOP。アカウント育成（20日でKarma 0→500）、シャドウBAN防止、フィンガープリントブラウザマトリックス、サブレディット選定、コンテンツテンプレート（90/10ルール）、Product Hunt × Redditフライホイール、AMA戦略をカバー。**重要な理由：Reddit コンテンツは ChatGPT/Claude のトレーニングデータの40.11%を占める英語 UGC 最大の情報源**。AFFiNE Redditキャンペーン3-4万インプレッション＋5-8% GitHubスター変換で実証。7つの実例（Adobe 3倍変換、Base44 $80M AMA、SenseNova-U1、Starterstory 0→3Kユーザー）。 🇰🇷 Reddit 마케팅 & 그로스 플레이북 — AI/SaaS 창업자를 위한 완전한 Reddit 운영 SOP. 계정 워밍업(20일 Karma 0→500), Shadow Ban 방지, 핑거프린트 브라우저 매트릭스, 서브레딧 선정, 콘텐츠 템플릿(90/10 룰), Product Hunt × Reddit 플라이휠, AMA 전략을 다룹니다. **지금 해야 하는 이유: Reddit 콘텐츠는 ChatGPT/Claude 학습 데이터의 40.11%를 차지하는 최대 영어 UGC 소스**. AFFiNE Reddit 캠페인 3-4만 노출 + 5-8% GitHub Star 전환으로 검증. 7가지 사례 연구(Adobe 3배 전환, Base44 $80M AMA, SenseNova-U1, Starterstory 0→3K 사용자). Triggers: "reddit marketing" | "reddit growth" | "reddit ads" | "reddit advertising" | "reddit strategy" | "reddit promotion" | "subreddit marketing" | "reddit playbook" | "reddit SOP" | "reddit shadow ban" | "shadow ban prevention" | "reddit karma" | "reddit AMA" | "reddit product launch" | "reddit AI training data" | "reddit GEO" | "AFFiNE reddit case" | "Base44 AMA" | "SenseNova Reddit" | "subreddit selection" | "r/SaaS posting" | "r/MachineLearning self-promotion" | "fingerprint browser matrix" | "AdsPower reddit" | "reddit account farming" | "reddit 90/10 rule" | "reddit content strategy" | "reddit indie founder" | "reddit cold start" | "Reddit 运营" | "Reddit 营销" | "Reddit 防封" | "Reddit 矩阵号" | "Reddit 出海" | "Reddit 引流" | "Reddit 冷启动" | "影子封禁" | "Reddit Karma" | "Reddit 养号" | "Reddit AMA" | "Reddit マーケティング" | "Reddit グロース" | "Reddit 마케팅" | "Reddit 그로스"