「theme」の検索結果

Synthesize qualitative and quantitative user research into structured insights and opportunity areas. Use when analyzing interview notes, survey responses, support tickets, or behavioral data to identify themes, build personas, or prioritize opportunities.

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Packages generated wiki Markdown into a VitePress static site with dark theme, dark-mode Mermaid diagrams with click-to-zoom, and production build output. Use when the user wants to create a browsable website from generated wiki 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。

Build dark-themed React applications using Tailwind CSS with custom theming, glassmorphism effects, and Framer Motion animations. Use when creating dashboards, admin panels, or data-rich interfaces with a refined dark aesthetic.

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Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance. Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building. USE FOR: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design, UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI. DO NOT USE FOR: Backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic without UI, or non-frontend code.

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Analyze Stockbee-style Day 1 Episodic Pivot candidates from earnings, guidance raises, M&A, FDA/regulatory approvals, analyst actions, major contracts, product launches, short-squeeze catalysts, or theme/story events. Scores catalyst quality together with gap/range expansion, volume shock, neglect/revaluation context, liquidity, and risk to the EP-day low. Use when the user asks for EP candidates, episodic pivots, Day 1 catalyst trades, game-changing news reactions, delayed EP watchlists, or handoffs into PEAD monitoring.

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Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.

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Use when the user asks to "map our positioning", "name our competitive alternatives", or "pick a beachhead segment for the launch"; produces a Dunford-style positioning canvas — named competitive alternatives (including spreadsheet and status quo), unique attributes (verifiable, or routed to the claims ledger), value themes (attribute→benefit→value chains), a target beachhead segment scored on serviceability / pain intensity / reachability, and a one-sentence onlyness statement — the sole upstream of the message house and the entity-signal source for the canonical entity profile. Not for the message house or per-channel launch copy — use message-house-builder; not for audience/persona profiling itself — use audience-mapper; not for SEO keyword positioning — use keyword-research. 定位画布/竞争替代品/独特价值/滩头细分

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当用户明确要求"从文件/图片/网页/描述中提取综述主题"、"生成主题+关键词+核心问题结构化输出"，或要求使用旧名 get-review-theme skill 时使用。支持文件（PDF/Word/Markdown/Tex）、文件夹、图片、自然语言描述、网页 URL 等多种输入源，自动识别输入类型并提取内容，生成可直接用于 research-literature-review 及其他文献综述技能的结构化输出。

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Design theming architecture — brand variants, dark mode, and high-contrast — mapped through token layers. Use when one system must serve multiple themes. For a single palette use `color-system` (ui-design); for dark mode craft use `dark-mode-design` (ui-design).

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Turn one interview transcript into themes, supporting quotes, and action items. Use immediately after a session. For synthesising many sessions at once, use `affinity-diagram`.

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Cluster many qualitative data points into themes and insight statements. Use when synthesising across multiple sessions or sources. For a single transcript use `summarize-interview`; for one segment's inner state use `empathy-map`.

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Build a Says, Thinks, Does, Feels map for one user or segment. Use when sharing user understanding quickly. For a composite archetype with goals and behaviours use `user-persona`; for cross-session themes use `affinity-diagram`.

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Audit and fix visual hierarchy, spacing, color, and depth in web UIs. Use when the user mentions "my UI looks off" (or amateur/unprofessional), "fix the design", "Tailwind styling", "color palette", "visual hierarchy", "design system", "spacing scale", or "component styling". Also trigger when building consistent design tokens, creating dark mode themes, improving data-visualization clarity, or polishing UI details before launch. Covers grayscale-first workflow, constrained design scales, shadows, and component styling. For typeface selection, see web-typography. For usability audits, see ux-heuristics.

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Use when configuring, running, or fixing PHPStan static analysis in WordPress projects (plugins/themes/sites): phpstan.neon setup, baselines, WordPress-specific typing, and handling third-party plugin classes.

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Use when working with WP-CLI (wp) for WordPress operations: safe search-replace, db export/import, plugin/theme/user/content management, cron, cache flushing, multisite, and scripting/automation with wp-cli.yml.

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Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.

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Convert Chinese stories or ordered local images into silent hand-drawn Remotion videos, with generated hand lettering, 327 built-in assets (297 style recipes and 30 theme palettes), a curated 30-style menu, and automatic reference-image style analysis with optional private reuse. Use when users ask to generate, import, restyle, preview or render hand-drawn story videos; browse or classify styles; imitate the visual grammar of a reference image; or save a reference-derived style. Preserve the approved colored-pencil diary default when no other style is requested.

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 professional Mermaid diagrams with multiple themes, SVG/ASCII output, batch rendering, and a built-in template library for common diagram patterns. Supports flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, C4 architecture, and Gantt charts.

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Generates complete process-related diagnostic biomarker bioinformatics research designs from a user-provided disease context, gene-family or pathway theme, and validation direction. Use when a study centers on process-related genes, DEG and WGCNA integration, machine-learning feature selection, nomogram-based diagnostic modeling, immune infiltration, regulatory-network analysis, and optional external or experimental validation. Covers five study patterns (process-DEG discovery, co-expression-module integration, machine-learning biomarker selection, diagnostic model/nomogram workflow, immune-regulatory interpretation and validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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Generates complete programmed-cell-death (PCD) / regulated-cell-death (RCD) bulk-transcriptome oncology research designs from a user-provided disease and mechanism theme. Always use this skill whenever a user wants to design, plan, or structure a cancer bioinformatics study built around cell-death patterns, tumor microenvironment, prognostic modeling, immune landscape analysis, mutation profiling, and computational drug sensitivity. Covers five study patterns (mechanism-gene-set, subtype-discovery, prognostic-signature, immune-response stratification, translational drug-hypothesis) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and a strictly verified reference literature retrieval layer with real references only.

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。

Generates complete conventional non-oncology diagnostic machine-learning research designs from a user-provided disease context, optional mechanism theme, and validation direction. Use when a study centers on disease-vs-control transcriptome comparison, optional mechanism-gene restriction, feature shrinkage, diagnostic model construction, ROC / calibration / DCA evaluation, interpretation layers, and orthogonal validation. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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。

Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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 evaluating top-down macro trades, liquidity regimes, currency/rates/equity themes, concentrated risk-taking, and quick loss-cutting in a Stanley Druckenmiller style.

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 evaluating Cathie Wood-style disruptive innovation themes: S-curves, converging technologies, long-duration growth, platform adoption, and multiyear innovation portfolios.

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。