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極繁主義網頁設計

將極繁主義作為網頁設計哲學——多即是多。密集的資訊佈局、多層次的視覺元素、混合字型、大膽的色彩碰撞、交錯的網格、圖案疊加,以及對極簡主義網頁慣例的刻意排斥。涵蓋彭博終端機美學、MySpace 懷舊風、日本網頁密度以及留白恐懼症。

極繁主義網頁設計 是什麼?

這項技能指導 AI 代理(如 Claude Code、Cursor、Codex 等)在網頁設計中擁抱密度、豐富性和視覺豐沛感,明確反駁「少即是多」的極簡主義。它為資料密集的儀表板(如彭博風格交易介面)或富有表現力的作品集(如 MySpace 懷舊風)提供結構化決策樹,包含資訊密度調整、動畫閾值控制、色彩衝突管理,以及「失明測試」等品質把關。此技能也明確界定其不適用的情境——例如政府網站或結帳流程,並建議改用其他專業技能——以防止 AI 產出無障礙或可用性不佳的設計。支援 Read、Write、Edit、Glob、Grep、WebSearch 和 WebFetch 工具,確保能根據使用者提示或現有程式碼環境進行全面實作與迭代。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/curiositech/windags-skills/tree/HEAD/skills/maximalist-web-design

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開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

license: Apache-2.0 name: maximalist-web-design description: 極繁主義作為網頁設計哲學——多即是多。密集的資訊佈局、多層次的視覺元素、混合字型、大膽的色彩碰撞、交錯的網格、圖案疊加,以及對極簡主義網頁慣例的刻意排斥。涵蓋彭博終端機美學、MySpace 懷舊風、日本網頁密度以及留白恐懼症。啟用關鍵詞:'極繁主義網頁'、'密集佈局'、'資訊密集'、'反極簡'、'多即是多'、'熱鬧設計'、'留白恐懼症'、'彭博美學'、'MySpace 美學'、'視覺過載'、'密集儀表板'。不可用於室內設計極繁主義(請改用 maximalist-wall-decorator)、新粗獷主義(請改用 neobrutalist-web-designer)、拼貼佈局(請改用 collage-web-design)。 allowed-tools: Read,Write,Edit,Glob,Grep,WebSearch,WebFetch metadata: category: 設計與使用者體驗 tags: - 極繁主義 - 密集佈局 - 資訊密度 - 反極簡 - 留白恐懼症 - 儀表板 - 網頁設計 - MySpace - 彭博 pairs-with: - skill: neobrutalist-web-designer reason: 共享反極簡哲學,可將粗框與密度結合 - skill: retrofuturism-web-design reason: 卡帶未來主義和異塵餘生介面本質上都是極繁主義 - skill: typography-expert reason: 極繁主義需要自信的多字型組合 - skill: hero-section-design reason: 極繁主義的英雄區塊需要精心編排以避免混亂 category: 設計與創意 tags:

  • 極繁主義
  • 網頁設計
  • 大膽
  • 折衷
  • 視覺

極繁主義網頁設計 是做什麼的?

創造擁抱密度、豐富性和視覺豐沛感的網頁體驗。極繁主義是刻意且熟練地拒絕「少即是多」——它主張多即是多,空白空間是浪費的空間,而視覺複雜性能在妥善編排下被瀏覽。

決策點

資訊密度決策樹

如果 viewport 寬度 > 1200px:
  └── 如果使用者以資料為中心(交易、分析、儀表板):
      ├── 資訊密度 > 80% 畫面 → 使用微卡片(8px 內邊距,0.75rem 文字)
      └── 資訊密度 60-80% → 使用密集網格(4px 間距,180px 最小寬度)
  └── 如果使用者為內容瀏覽(作品集、編輯類):
      ├── 視覺衝擊優先 → 使用 20-30% 重疊的分層卡片
      └── 可讀性優先 → 使用 1.5rem 間距的欄位佈局

如果 viewport 寬度 768-1199px:
  └── 密度降低 30%:
      ├── 將側邊欄折疊為圖示
      └── 切換為最多 2 欄的網格

如果 viewport 寬度 < 768px:
  └── 單欄,觸控目標增加至最小 44px

動畫閾值決策樹

如果 viewport 中同時動畫數 > 3:
  └── 減少為最多 2 個元素同時移動

如果動畫持續時間 > 1.5 秒:
  └── 加入懸停暫停以提供使用者控制

如果使用者有動作敏感:
  └── 替換為 CSS 轉場(持續時間 < 0.3s)
  └── 僅使用 transform/opacity(避免佈局抖動)

色彩衝突管理

如果背景-前景對比度 < 4.5:1:
  └── 在文字後方加入半透明疊加層
  └── 或從調色盤切換為高對比色對

如果在單一組件中使用超過 5 種顏色:
  └── 指派語意角色(主要、次要、強調、中性、警告)
  └── 使用色盲模擬器測試可及性

如果顏色感覺混亂(使用者回饋):
  └── 建立色彩區域——將相關內容歸入相同色系
  └── 使用 70-25-5 規則:70% 主導色、25% 次要色、5% 強調色

失敗模式

易引發癲癇的動畫過載

症狀: 多個元素同時動畫、快速閃爍效果、無暫停控制 檢測: 如果同時移動元素 > 3 個,或任何閃爍頻率 > 3Hz,或未支援 prefers-reduced-motion 修復: 最多限制 2 個並行動畫,加入懸停暫停,實作動畫減少查詢

難以辨識的文字瘟疫

症狀: 使用者抱怨可讀性,文字融入雜亂背景,內容參與度低 檢測: 對比度 < 4.5:1,密集背景上文字小於 14px,顏色衝突 修復: 在文字後方加入半透明背景,增加字重,切換為高對比色對

資訊架構崩潰

症狀: 使用者找不到關鍵操作,所有元素看起來同等重要,高跳出率 檢測: 無清晰視覺層級(瞇眼測試失敗),所有元素大小/重量相同,無色彩區域 修復: 實作標題/內文 4:1 尺寸比例,建立色塊區域,加入不透明層級 (1.0/0.7/0.4)

行動觸控目標失敗

症狀: 行動使用者感到挫折,誤觸,在觸控裝置上無法使用 檢測: 行動裝置上互動元素 < 44px,依賴懸停的互動,僅限桌機的密度 修復: 行動觸控目標增加至最小 44px,加入行動專用間距,實作漸進式密度

實作範例

範例 1:彭博風格交易儀表板

情境: 金融交易平台需要最大資訊密度,同時維持瞬間可用性。

初始評估: 使用者需要同時監控 50 個以上資料點,主要裝置為具備大螢幕的桌機,使用者為熟悉密度的專業交易員。

設計決策:

  1. 資訊密度: 85% 畫面覆蓋率(因超過 80% 密度門檻而選擇微卡片)
  2. 字型: 所有數字使用等寬字型 (IBM Plex Mono),標籤使用窄版無襯線字型 (Barlow Condensed)
  3. 色彩系統: 彭博調色盤——終端機黑色背景,主要資料使用琥珀色,方向變化使用綠色/紅色
  4. 動畫: 僅以 0.3 秒高亮淡入淡出動畫價格變動,無並行動畫

實作策略:

.trading-grid {
  display: grid;
  grid-template-columns: repeat(auto-fill, minmax(160px, 1fr));
  gap: 2px;
  padding: 4px;
  height: 100vh;
  overflow-y: auto;
}

.price-card {
  background: #1E1E1E;
  border: 1px solid #2A2A2A;
  padding: 6px;
  font-family: 'IBM Plex Mono', monospace;
  font-size: 0.7rem;
}

.price-change {
  transition: background-color 0.3s ease;
}

做出的取捨:

  • 為資訊密度犧牲視覺吸引力(選擇功能重於形式)
  • 接受新使用者的陡峭學習曲線(優先考量專家使用者)
  • 為桌機最佳化而限制行動體驗

範例 2:MySpace 懷舊風作品集網站

情境: 創意專業人士想要一個能捕捉 2000 年代初期網路精神,同時展示現代作品的個人作品集。

初始評估: 內容混合(圖片、文字、影片),目標觀眾為欣賞大膽風格的同儕創作者,主要目標為留下令人印象深刻的記憶,而非易用性。

設計決策:

  1. 資訊密度: 65% 畫面覆蓋率(選擇具有視覺重疊的分層卡片)
  2. 字型: 混合系統——標題使用 Abril Fatface,內文使用 Space Grotesk,說明文字使用 IBM Plex Mono
  3. 色彩系統: 電光極繁主義調色盤——紫羅蘭主色,珊瑚色次要,酸黃色強調
  4. 動畫: 微妙的視差滾動、懸停變形、交錯入場動畫

混亂控制策略:

  • 色彩區域: 每個專案區塊使用不同的背景色調以建立區隔
  • 視覺層級: 專案標題與描述之間 4:1 的尺寸比例
  • 控制性重疊: 元素精確重疊 20%,創造節奏而非隨機性
  • 喘息空間: 每三個區塊就有一個密度降低 80%,提供視覺休息

解決的關鍵問題: 如何讓極繁主義感覺是刻意的,而非偶然 解決方案: 使用數學關係(20% 重疊、4:1 比例、70-25-5 色彩分配)在混亂中建立秩序

品質把關

  • 瞇眼測試通過:半閉眼時可看見 3 個不同的層級
  • 所有內文對比度 ≥ 4.5:1(以實際背景圖案測量)
  • 行動裝置上所有互動元素的觸控目標 ≥ 44px
  • 任何 viewport 中最多同時 2 個並行動畫
  • 已實作並測試 prefers-reduced-motion 查詢
  • 色彩區塊清楚區分不同內容區域
  • 字型使用 ≥ 3 個字型家族,並指定不同的語意角色
  • 行動版佈局密度比桌機版至少降低 30%
  • 符合效能預算:即使 DOM 密集,首次內容繪製 < 2 秒
  • 至少提供一個「逃脫閥」(可折疊面板、專注模式或篩選器)

不適用邊界

請勿將 maximalist-web-design 用於:

  • 需要無障礙合規的政府或醫療網站 → 請改用 accessibility-first-design
  • 電子商務結帳流程 → 請改用 conversion-optimization-expert 以獲得簡化的流程
  • 室內設計極繁主義 → 請改用 maximalist-wall-decorator 處理實體空間
  • 新粗獷主義的扁平色粗框風格 → 請改用 neobrutalist-web-designer 獲得該美學
  • 編輯拼貼重疊構圖 → 請改用 collage-web-design 處理雜誌版面
  • 企業 SaaS 應用程式 → 請改用 web-design-expert 處理商業軟體介面
  • 為轉換率最佳化的登陸頁面 → 極繁主義與轉換目標相悖

在以下情況委派給其他技能:

  • 客戶提到「乾淨專業」 → web-design-expert
  • 專案需要 WCAG AAA 合規 → accessibility-first-design
  • 預算限制需要快速開發 → bootstrap-expert
  • 需要定義內容策略 → content-strategist

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

curiositech/windags-skills

Expert in 2000s-era music visualization (Milkdrop, AVS, Geiss) and modern WebGL implementations. Specializes in Butterchurn integration, Web Audio API AnalyserNode FFT data, GLSL shaders for audio-reactive visuals, and psychedelic generative art. Activate on "Milkdrop", "music visualization", "WebGL visualizer", "Butterchurn", "audio reactive", "FFT visualization", "spectrum analyzer". NOT for simple bar charts/waveforms (use basic canvas), video editing, or non-audio visuals.

curiositech/windags-skills

Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape.

curiositech/windags-skills

Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

curiositech/windags-skills

Implement WCAG 2.2 AA/AAA compliance with automated testing, keyboard navigation, screen reader support, and focus management. Activate on: accessibility audit, WCAG compliance, keyboard navigation, screen reader, aria attributes, axe-core, focus trap. NOT for: design-level accessibility review (use design-accessibility-auditor), color contrast only (use css-in-js-architect).

curiositech/windags-skills

Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.

curiositech/windags-skills

Designs digital experiences for ADHD brains using neuroscience research and UX principles. Expert in reducing cognitive load, time blindness solutions, dopamine-driven engagement, and compassionate design patterns. Activate on 'ADHD design', 'cognitive load', 'accessibility', 'neurodivergent UX', 'time blindness', 'dopamine-driven', 'executive function'. NOT for general accessibility (WCAG only), neurotypical UX design, or simple UI styling without ADHD context.

curiositech/windags-skills

>- Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.

curiositech/windags-skills

Extend and modify the admin dashboard, developer portal, and operations console. Use when adding new admin tabs, metrics, monitoring features, or internal tools. Activates for dashboard development, analytics, user management, and internal tooling.

curiositech/windags-skills

Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-patterns).

curiositech/windags-skills

Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).

curiositech/windags-skills

AI-powered calendar management and agent-based scheduling coordination. Covers calendar APIs (Google Calendar, CalDAV/iCal), AI scheduling assistants (Reclaim, Clockwise, Motion, Cal.com), building custom calendar agents with MCP, multi-calendar merging, timezone management, focus block protection, meeting fatigue detection, and agent-to-agent meeting negotiation protocols. Activate on: "calendar agent", "AI scheduling", "calendar coordination", "meeting scheduling", "calendar API", "focus time protection", "calendar optimization", "Google Calendar MCP", "Reclaim", "Clockwise", "Motion", "Cal.com", "smart scheduling", "calendar-aware agent", "timezone scheduling", "agent negotiation meetings". NOT for: manual calendar UI component design (use form-validation-architect), project management scheduling or Gantt charts (use project-management-guru-adhd), general time-tracking or pomodoro apps (use adhd-daily-planner for time-awareness), building the agent itself from scratch (use agent-creator).

curiositech/windags-skills

Build and adopt production AI agent infrastructure in 2026. Covers framework selection (LangGraph, CrewAI, AutoGen, MCP), orchestration patterns, evaluation, observability, memory systems, and tool use. Also covers the SOCIAL dimension: how to sell agent infrastructure internally, change management, measuring ROI, building trust in autonomous systems, and scaling adoption across teams. Activate on: "agent infrastructure", "agent framework comparison", "which agent framework", "sell AI tools internally", "agent adoption", "agent observability", "agent evaluation", "MCP architecture", "agentic mesh", "enterprise AI agents", "AI change management", "agent ROI". NOT for: building specific agents (use ai-engineer), designing agent behavior patterns (use agentic-patterns), prompt tuning (use prompt-engineer).

curiositech/windags-skills

Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use windags-architect), specific tool implementation.

curiositech/windags-skills

Automated discovery and matching of agent skills for dynamic task routing and capability assessment

curiositech/windags-skills

Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).

curiositech/windags-skills

Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Deep comparison of A2A protocol, MCP, OpenAI function calling, and LangChain message types. Teaches when to use rigid schemas vs free-form with validation, typed vs untyped, streaming vs batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).

curiositech/windags-skills

Logic-based agent programming language implementing BDI architecture for practical autonomous agent development

curiositech/windags-skills

>- Design AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.

curiositech/windags-skills

Foundational concurrent computation model where actors communicate exclusively through asynchronous message passing

curiositech/windags-skills

license: Apache-2.0 NOT for unrelated tasks outside this domain.

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