「stitch」の検索結果

Iterative design-to-code feedback loop. Critique → adjust → ship cycle for tightening visual fidelity between brief and built UI.

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。

When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.

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。

Brand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens — use frontend-design instead.

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 guidance for integrating and building applications with shadcn/ui components, including component discovery, installation, customization, and best practices.

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。

Capture or repair reliable full-page screenshots for lazy-loaded, scroll-animated, Framer, WebGL/canvas, or reveal-heavy web pages. Use when full-page screenshots are blank, gray, white, sparse, show a tiny content strip, disagree with a working scroll video, or when article evidence/section crops must be derived from a trustworthy full-page 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。

Build convincing woven cloth in Three.js, with a thread-level weave normal map, sheen and anisotropic highlights, folds that never stretch the texture, hems with thickness, stitches, seams, frayed edges, fold occlusion, dye and wear variation, and light passing through thin fabric. Use for linen, silk, wool, canvas, curtains, banners, cloaks, tablecloths, tapestries or any 3D drape that currently looks like a plastic sheet, a stretched texture, or a flat coloured plane.

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。

Clean, high-contrast enterprise design for data-driven workflows with intuitive drag-and-drop patterns and structured layouts.

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。

AI design specialist skill with DESIGN.md management, anti-pattern enforcement, optional Stitch MCP integration, and component library guidance. Covers typography, color systems, motion design (motion/react, GSAP, Three.js), responsive-first layouts, and accessibility (WCAG 2.2).

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。

the UGC fix-loop toolkit — surgically re-render a bad window/beat of a single-take UGC master (stitch_replacement.py, pure FFmpeg) and GPT cross-model review a Seedance prompt before render (vet_seedance_prompt.py, routed through the openai-proxy). Fetch it into a one-shot UGC recipe so both scripts resolve on any machine and the vet call bills the Ads agent.

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。

Identifies super-enhancers from H3K27ac, MED1, or BRD4 ChIP-seq using ROSE, ROSE2, LILY, HOMER -style super, and ENCODE dELS cross-referencing. Handles peak stitching parameters, ranking choices, hockey-stick inflection, marker choice (H3K27ac vs MED1/BRD4), and cross-condition comparison with spike-in normalization. Constructs core regulatory circuitry (Saint-Andre 2016) from SE-encoded TFs. Use when identifying cell-identity / cancer-associated regulatory domains, comparing super-enhancers between conditions, identifying master transcription factor networks, or predicting BET-inhibitor responsiveness.

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。

Load this first for any task involving images, pictures, photos, scans, frames, volumes, or visual data — including reading, writing, filtering, enhancing, denoising, sharpening, deblurring, thresholding, segmenting, masking, detecting, finding or counting objects, removing backgrounds, measuring, comparing, registering, stitching, aligning, cropping, resizing, transforming, or analyzing. Use for image I/O (TIFF, PNG, JPEG, RAW, HDR), histograms, edge detection, color processing, morphology, geometric transforms, deep learning for images, quality assessment, and 3-D volume processing. Also triggers when users describe image problems (dark, noisy, blurry, low contrast, uneven lighting, hazy, color cast) or data exploration tasks (folder of images, characterize data, understand format). Handles microscopy (cells, particles) and general scientific imaging. Routes to sibling skills for medical imaging (DICOM, NIfTI), hyperspectral data, and visual inspection.

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 generated clips must become a finished video on Scenario via MCP: cutting a shot list together, laying a timeline, concatenating with transitions, overlaying a logo or title card, adding a music bed or voiceover, burning in or exporting captions and subtitles, trimming and splitting, or producing vertical and square variants of one master. Keywords: edit, assemble, stitch, concat, compositor, timeline, layers, overlay, captions, SRT, ad, UGC, social cut.

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。

How to actually instrument product analytics correctly. Event taxonomy, property design, naming conventions, schema versioning, identity stitching, funnel design, retention cohorts, North Star metric selection, dashboard hygiene, instrumentation debt, and the failure modes that produce data nobody trusts. Triggers on product analytics setup, event taxonomy, tracking plan, instrumentation, schema versioning, North Star metric, retention cohorts, funnel design, naming conventions, instrument new feature, audit existing analytics, dashboard reconciliation, instrumentation debt, Mixpanel setup, Amplitude setup, PostHog setup, warehouse-native analytics. Also triggers when the team has data but cannot trust it, or when designing instrumentation for a new feature, or when auditing an existing setup that has drifted.

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。

When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.

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。

Volcengine VOD audio and video processing tools skill. Use when users need VOD-based media processing or editing: upload local/URL media, stitch videos, trim clips, flip frames, change playback speed, create image-to-video, compose audio/video, extract audio, mix audio, separate vocals/accompaniment, denoise audio, enhance quality, AI super-resolution, frame interpolation, ASR speech-to-text, OCR text extraction, subtitle removal, subtitle embedding, scene slicing, portrait/green-screen matting, highlight extraction, comic style transfer, video translation, drama recap narration, drama script restoration, media info lookup, or playback URL retrieval. The skill submits async VOD jobs, polls task status, and returns generated output links. Not for pure text generation, real-time streaming, or source-free generative video creation.

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 Chinese classical poems and ci into coherent vertical Chinese-art videos with poem-driven scene grouping, GPT ImageGen stills, Docker-only Gemini I2V, retained model-generated ambience, Gemini sparkle-watermark cleanup, brush-calligraphy captions revealed character by character, optional local BGM mixing, stitching, and final-frame QA. Supports verse-driven variation across ink landscape, gongbi bird-and-flower, colored figure-and-horse painting, blue-green landscape, xuan paper, silk, and related Chinese visual languages. Use when users ask for 古诗词动态视频、诗词逐句或两句一景、国风视频、毛笔字逐字出现、整首诗拼接成片，or want the established 月落乌啼霜满天 workflow applied to another poem.

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。

Combines GIFs and videos into composite tutorials with vertical or grid layouts via ffmpeg. Use when assembling multi-part media into a single output.

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 this skill to plan, direct, finish, and QA provider-independent mono or stereo 180-degree, 360-degree, spherical, spatial, wide-FOV, and immersive video. It covers format choice, capture rigs, stitching, nadir and seam management, stereoscopic comfort, attention direction, stabilization, ambisonic and spatial audio, titles, captions, accessibility, edit, color, VFX, projection metadata, Vision Pro, YouTube, headset delivery, device QA, and privacy, location, and likeness rights. Do not use it for interactive XR apps, volumetric/world-model generation, game-engine experiences, or provider-specific video generation prompts.

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 teach / learn an English word as a video — turn a single English word into a self-contained HLS "supercut" lesson built from the mira video base. Stitches every season2 clip where the word is spoken (via the search-app API) into one .m3u8, prepended with a Claude-written bilingual word-intro card (word + IPA + 中文 gloss + usage, Volcano TTS) and appended with a 关注王建硕 CTA card. No MP4 burn. Triggers — "teach <word>", "讲讲 <word>", "学英语 <word>", "把 <word> 做成视频", "/wjs-teaching-english <word>".

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。

Compare captures; stitch lazy/animated pages.

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。

Suede-owned marketing attribution discipline. Use when the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions 'attribution,' 'attribution model,' 'first-touch vs last-touch,' 'multi-touch,' 'which channel drives revenue,' 'what's my real CAC,' 'my dashboards disagree,' 'Google/Meta says X but GA says Y,' 'MMM,' 'incrementality,' 'geo lift,' 'holdout test,' 'how did you hear about us,' 'self-reported attribution,' 'dark social,' or wants to instrument attribution themselves, 'stitch my bookings to their source,' 'SavvyCal/Calendly attribution,' 'close the identify gap,' 'track conversions on a third-party domain,' 'first-party attribution.' NOT FOR: general analytics instrumentation and reporting (use suede-analytics) or revenue-ops pipeline work (use suede-revops).

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。

Write a TikTok caption under 2,200 chars (hashtags included), pick a tasteful 3 to 5 hashtag set with mixed reach, and set the platformSettings.tiktok flags (viewer setting, comments, duet, stitch, commercial and branded content). Front-loads a reason to comment, runs the humanizer pass, and publishes the rendered video via Publora on approval. Use to caption a finished video. Not for the in-video hook (use tt-hook-scripter) or scrubbing a script (use tt-humanizer).

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。

Ultimate Design System Intelligence. Manage, extract, replicate, and improve UI design systems. Extracts design tokens visually from existing sites (Harvester v5), manages multi-page tokens, and utilizes MCP servers like Google Stitch and Pencil.dev to generate complete, consistent design systems (Shadcn UI, Halo, Lunaris, Nitro). Use when the user asks to "extract design from a URL", "create a Shadcn design system", "analyze design tokens", "build a design system for", or "copy the UI style of".

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。

Ultimate UI/UX design intelligence: an Anti-Slop layer that kills AI tells (em-dash, AI purple glow, generic names, template layouts), tunable Design Dials (variance/motion/density) and Style Modes (functional, minimalist, brutalist, soft-premium, marketing), 161 industry color palettes in a shadcn-aligned semantic token schema, 48 UX Laws, 37 Design Tests, UX Heuristics (Nielsen + Krug), Harvester extraction, Figma & Google Stitch integration, MCP server, Component Generator, and BM25 search across 17 domains + 19 framework stacks. One command = complete design system. Use when designing or reviewing UI/UX, choosing colors/typography, fixing generic AI-looking designs, or building Web App / SaaS / Mobile screens.

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。