3,133 件 ・ 関連度順
概要と使いどころ
Mantém coerência visual entre peças geradas por IA — seed, modelo fixo, referência de estilo e biblioteca de prompts da marca. Use quando o usuário disser "as peças não parecem da mesma campanha", "manter o estilo", "consistência", "cada imagem saiu diferente", "padronizar o visual gerado". É o problema mais difícil de geração por IA em escala.
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。
Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use /plan-design-review. Use when asked to "audit the design", "visual QA", "check if it looks good", or "design polish". Proactively suggest when the user mentions visual inconsistencies or wants to polish the look of a live site. (gstack)
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。
Visualize biological networks (PPI, gene-regulatory, co-expression, pathway) with layout algorithm choice (ForceAtlas2, Fruchterman-Reingold, Kamada-Kawai, hive plots), edge bundling, community-based coloring, and reproducible seeds using NetworkX, PyVis, igraph, and Cytoscape automation. Use when rendering biological networks for static publication, interactive HTML exploration, or Cytoscape-format export.
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。
Visualize copy number profiles, segments, allele-specific tracks, and cohort patterns from CNVkit, GATK, ASCAT, FACETS, Sequenza, and other callers. Covers genome-wide and per-chromosome log2 scatter plots, B-allele-frequency/minor-allele-fraction tracks, ideograms, cohort heatmaps, circos views, and caller-native plots. Use when creating publication CNV figures, choosing which plot answers a given question, diagnosing a wrong diploid baseline visually, displaying loss of heterozygosity, or deciding what depth-only plots cannot reveal.
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。
Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap (ComplexHeatmap-based), ChIPseeker tag heatmaps, and IGV batch screenshots. Handles bigWig normalization choices (CPM, BPM, RPGC, spike-in scaled), bamCompare operations (log2 ratio, subtract, SES), k-means clustering of heatmaps for biological subgrouping, and spike-in-scaled tracks for global-shift experiments. Use when generating publication-quality ChIP-seq signal heatmaps, profile plots, genome-browser tracks, or comparing samples visually.
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。
Improve layout, spacing, and visual rhythm. Fixes monotonous grids, inconsistent spacing, and weak visual hierarchy. Use when the user mentions layout feeling off, spacing issues, visual hierarchy, crowded UI, alignment problems, or wanting better composition.
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 Three.js, 3D graphics, and interactive 3D visualizations
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。
Production pipeline for ASCII art video — any format. Converts video/audio/images/generative input into colored ASCII character video output (MP4, GIF, image sequence). Covers: video-to-ASCII conversion, audio-reactive music visualizers, generative ASCII art animations, hybrid video+audio reactive, text/lyrics overlays, real-time terminal rendering. Use when users request: ASCII video, text art video, terminal-style video, character art animation, retro text visualization, audio visualizer in ASCII, converting video to ASCII art, matrix-style effects, or any animated ASCII 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。
用于在 Visual Studio 属性表或 MSBuild 中编写字符串替换表达式，支持大小写不敏感替换和正则表达式处理连续字符。
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。
根据用户指定的数学规则（如取整、特定尾数四舍五入），生成用于批量修改AutoCAD图元（如直线、多段线）坐标值的VisualLISP代码。
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。
用于配置 Visual Studio 属性表（.props），通过设置绝对路径解决项目引用后 DLL 运行时找不到的问题，且不修改全局环境变量，实现引入即用。
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 professional posters and visual designs using AI image generation. Supports event posters, product showcases, announcements, and social media graphics. Integrates with Gemini image generation API to create visuals based on templates and user content. Use when the user wants to design posters, generate marketing visuals, create promotional materials, or produce image-based content for events, products, or announcements.
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。
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
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。
Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps, sentence-case typography, and automatic dark mode. Best suited for educational and non-software visuals — physics setups, chemistry mechanisms, math curves, physical objects (aircraft, turbines, smartphones, mechanical watches), anatomy, floor plans, cross-sections, narrative journeys (lifecycle of X, process of Y), hub-spoke system integrations (smart city, IoT), and exploded layer views. If a more specialized skill exists for the subject (dedicated software/cloud architecture, hand-drawn sketches, animated explainers, etc.), prefer that — otherwise this skill can also serve as a general-purpose SVG diagram fallback with a clean educational look. Ships with 15 example diagrams.
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, critique, or specify honest charts and data visualizations from known data and audience needs. Use for chart selection, misleading-chart audits, accessibility, dashboard visuals, or "make this data easier to understand"; do not use for raw data analysis, PPT deck generation, spreadsheet surgery, or fabricated chart data.
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。
Personal AI agent visual diary. Auto-records all agent activity, generates daily narrative summaries, visual timeline replay, and AI first-person journal. Use /diary for today's summary, /diary:thoughts for AI personal journal, /diary:replay for visual timeline, /diary:stats for analytics, /diary:persona to view/edit AI personality.
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。
Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus the music file the finished video must carry. Your audio never reaches the API (measured) — the visuals are written to the track's tempo, mood and sections, then your own file is laid on locally at zero cost. One job caps at 30 seconds, so a three-minute song is six jobs minimum and the cost table says that before anything is spent. Use when a user has a specific piece of music and wants visuals for it, e.g. "make a music video for this track", "visuals for my song", "an MV for this instrumental", "generate footage cut to this beat". Do not use for cheap vertical social drafts (shorts-reels), a brand film that happens to have a music bed (seedance-ad-creative), or when there is no particular audio file the finished video has to carry.
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 brand visual system from a website or brand assets into a structured style guide
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 turning data visualizations into compelling video and animation content for social media and marketing. Activate on: data commercial, animated chart, data storytelling video, chart animation, Remotion data video, Motion Canvas, Flourish animation, D3 animation, data viz social media, dashboard recording, data narrative video. NOT for: static data visualization (use data-viz-2025), general video editing (use video-processing-editing), full video production pipeline (use ai-video-production-master).
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 modern, intuitive DAG/workflow visual editors that feel like LEGO, not LabView NOT for runtime DAG admission, graph execution, or claiming usability without user testing.
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。
Telegramのテスト環境で実ユーザーとしてOpenClawを操作し、応答や編集・削除・リアクションなどを記録して、利用者に見える動作を検証するスキル。
新しい機能や企画を作り始める前に、対話で目的や希望、制約を整理します。必要に応じて図や試作品で認識を確かめ、作業の規模に合った設計をまとめるスキルです。
動画・音声をVideoDBに取り込み、発話や映像から場面を検索して切り抜きを作成。字幕や音声の追加、画面比率の変換、ライブ映像の通知設定も支援します。
参考素材の見た目やカットのリズムを再利用できる設定に整理し、手元の映像の編集計画、画像・動画・3D素材の生成計画、編集可能なタイムラインをオフラインで作るスキル。