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curiositech/windags-skills

為網頁應用程式、行動應用程式和桌面原生應用程式的音效設計提供決策指南,涵蓋何時使用、使用何種聲音,以及如何利用 AI 製作。

windags-skills 是什麼?

此技能專注於 UI 音效設計,協助開發者判斷應用程式中哪些互動需要聲音回饋,以及如何選擇適當的聲音類型(如確認音、警示音、轉場音效)。它詳細比較 iOS、macOS 和 Material Design 的平台慣例,並提供使用 ElevenLabs、AudioCraft 和 Stable Audio 等 AI 工具生成 UI 聲音的實用範例。此外,技能還涵蓋 Web Audio API 的程式化聲音生成、觸覺-音頻配對方法,以及令人滿意與惱人 UI 聲音的心理學原理。支援的平台包括網頁、iOS、Android 和桌面應用,特別適合需要提升產品聲音品質但非專業音訊工程的開發者。

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

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

應用程式音效設計

負責做出關於應用程式中何時、使用何種聲音以及如何呈現的設計決策。這不是關於音訊工程(那是 sound-engineer)或復古音效(那是 win31-audio-design)。此技能回答 UI 音效中最困難的問題:這個互動到底該不該有聲音? 如果該有,那要用什麼樣的聲音?

使用時機

適合使用於:

  • 決定網頁或行動應用程式中哪些互動需要聲音回饋
  • 為通知、確認、錯誤等選擇合適的聲音特性
  • 使用 ElevenLabs、AudioCraft 或 Stable Audio 建立 AI 生成的 UI 音效
  • 使用 Web Audio API 實作程式化音效
  • 在 iOS/Android 上配對觸覺回饋與音訊
  • 為產品建立聲音品牌識別
  • 審查應用程式現有音效設計,判斷其是令人惱火還是有所幫助

請勿使用於:

  • 專業音訊混音/母帶處理 -> 請使用 sound-engineer
  • Windows 3.1 主題系統音效 -> 請使用 win31-audio-design
  • 音樂創作或配樂 -> 請使用 sound-engineer
  • 無障礙螢幕閱讀器音訊 -> 請使用 accessibility-expert
  • 遊戲音訊系統(3D 定位、動態音樂) -> 請使用 sound-engineer

基本問題:該不該有聲音?

這個互動是否需要「回饋」?
|
+-- 使用者發起的動作(點按、點擊、提交)?
|   +-- 結果是否在螢幕上可見?
|   |   +-- 是且很明顯 --> 聲音是「可選的」(通常略過)
|   |   +-- 是但很細微 --> 聲音「有幫助」(溫和確認音)
|   |   +-- 否(背景處理) --> 「建議」使用聲音
|   +-- 動作是否具有破壞性?
|       +-- 是 --> 「建議」使用聲音(明顯的警告音)
|       +-- 否 --> 聲音是「可選的」
|
+-- 系統發起的事件(通知、警示)?
|   +-- 使用者是否在應用程式內?
|   |   +-- 是 --> 微弱的應用程式內部音效
|   |   +-- 否 --> 通知音效(遵循作業系統慣例)
|   +-- 事件是否具有時效性?
|       +-- 是 --> 更緊急/引人注意的聲音
|       +-- 否 --> 可以靜音或使用環境音
|
+-- 環境/氛圍(背景狀態)?
    +-- 應用程式是否需要存在感? --> 微弱的環境音
    +-- 使用者是否正在工作/專注? --> 靜音

UI 音效詞彙

每個應用程式都需要來自這些類別的聲音。並非所有類別都是必要的 – 大多數應用程式需要 3-5 種。

第一層:必備(大多數應用程式需要)

聲音類型用途特性持續時間範例
確認音動作成功明亮、上升的音高100-300 毫秒Slack 訊息已傳送
錯誤音動作失敗低沉、平直或下降200-400 毫秒表單驗證失敗
通知音新資訊送達明確、中等能量300-600 毫秒Slack 新進訊息

第二層:精緻化(重視細節的應用程式)

聲音類型用途特性持續時間範例
轉場音檢視之間導航微弱的咻聲或輕點聲50-150 毫秒iOS 翻頁效果
切換音二進位狀態變更清脆的點擊聲或喀嚓聲50-100 毫秒開關切換
懸浮音滑鼠懸停回饋幾乎聽不見的滴答聲20-50 毫秒選單項目懸停
選擇音從列表中選擇項目輕柔的波普聲或撥弦聲50-150 毫秒下拉選單選擇
刪除音破壞性移除空洞的重擊聲或颼颼聲150-300 毫秒垃圾桶動作

第三層:愉悅感(有個性的應用程式)

聲音類型用途特性持續時間範例
成就音達到里程碑音樂性、慶祝感500 毫秒-2 秒Duolingo 課程完成
環境音背景存在感循環、氛圍感連續Noisli、Forest 應用程式
品牌音應用程式開啟/關閉標誌性、令人難忘500 毫秒-1.5 秒Netflix 噠噠聲
彩蛋音隱藏樂趣俏皮、出乎意料可變Konami 密碼獎勵

平台慣例

Apple(iOS / macOS)

Apple HIG 規範了特定的音訊行為:

  • 系統聲音是神聖的:切勿覆寫或取代系統警示音
  • 尊重靜音開關:如果實體靜音開關開啟,您的應用程式聲音就會停止(媒體播放除外)
  • 音訊工作階段類別很重要:
    • ambient — 與其他音訊混合,尊重靜音開關
    • soloAmbient — 使其他音訊靜音,尊重靜音開關
    • playback — 忽略靜音開關(僅適用於媒體應用程式)
  • 觸覺回饋與聲音配對:使用 UIImpactFeedbackGenerator 搭配音訊

Apple 的聲音特性:

  • 乾淨的正弦波和濾波音調
  • 最少的泛音(純淨、不刺耳)
  • 短衰減(聲音不會持續)
  • 相對於系統聲音的一致音量
// iOS:播放系統聲音
import AudioToolbox
AudioServicesPlaySystemSound(1057) // 標準鍵盤點擊聲

// iOS:觸覺回饋 + 自訂聲音
let generator = UIImpactFeedbackGenerator(style: .light)
generator.impactOccurred()
// 同時播放您的自訂聲音

Material Design(Android)

Google 的聲音設計原則:

  • 功能性優先:聲音應告知,而非裝飾
  • 預設為細微:UI 聲音應比媒體聲音小聲
  • Android 上觸覺優先:偏好觸覺回饋;僅在觸覺不足時才添加聲音
  • 僅在有意義時才開啟聲音:大多數互動的預設狀態應為靜音

Material 聲音特性:

  • 短促、清脆的打擊樂聲
  • 微妙的泛音內容(非純正弦波)
  • 比 Apple 聲音稍溫暖(更多中頻)
  • 設計用於在低品質手機喇叭上正常運作

網頁應用程式

網頁的聲音慣例最弱,這意味著有更多自由,但也更容易令人惱火。

  • 絕不自動播放聲音 — 瀏覽器會封鎖,使用者會討厭
  • 需要使用者手勢先行:Web Audio API 需要使用者互動才能播放
  • 提供音量控制:務必讓使用者可以靜音或調整
  • 考慮耳機使用者:在筆電喇叭上聽起來不錯的聲音,在耳機上可能很刺耳

使用 AI 建立音效

ElevenLabs 音效

最適合:具有特定特性描述的真實、高品質 UI 音效。

# 產生確認鈴聲
curl -X POST "https://api.elevenlabs.io/v1/sound-generation" \
  -H "xi-api-key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Sh 短促明亮的上行鈴聲、數位音、乾淨的正弦波、200 毫秒、UI 確認音效",
    "duration_seconds": 0.5
  }'

ElevenLabs 的有效提示:

  • 確認音:"Short bright ascending two-note chime, clean digital, warm, 200ms"
  • 錯誤音:"Low hollow thud with slight buzz, digital, 300ms, not harsh"
  • 通知音:"Gentle three-note xylophone melody, friendly, 400ms"
  • 切換音:"Crisp mechanical click, plastic switch, 50ms"
  • 刪除音:"Soft hollow swoosh moving downward, 200ms"
  • 成就音:"Bright ascending arpeggio, sparkly, celebratory, 1 second"

Meta AudioCraft(開源)

最適合:想要完全控制且無 API 費用的開發者。

from audiocraft.models import AudioGen
from audiocraft.data.audio import audio_write

model = AudioGen.get_pretrained('facebook/audiogen-medium')
model.set_generation_params(duration=0.5)

# 生成 UI 音效
descriptions = [
    "short digital confirmation beep, ascending pitch, clean",
    "low error buzz, brief, not harsh, digital",
    "gentle notification chime, two notes, pleasant",
]

wav = model.generate(descriptions)
for i, w in enumerate(wav):
    audio_write(f'ui_sound_{i}', w.cpu(), model.sample_rate)

Stable Audio Open

最適合:較長的環境音、背景紋理、品牌音。

import torch
from stable_audio_tools import get_pretrained_model
from stable_audio_tools.inference.generation import generate_diffusion_cond

model, model_config = get_pretrained_model("stabilityai/stable-audio-open-1.0")

# 生成環境背景音
conditioning = [{
    "prompt": "calm ambient digital texture, warm low hum, suitable for productivity app background, loopable",
    "seconds_total": 10
}]

後製檢查清單

AI 生成的音效在上線前需要清理:

  1. 修剪靜音 — 移除開頭/結尾的空白音訊
  2. 歸一化音量 — 所有 UI 音效應具有一致的感知響度
  3. 淡入/淡出 — 5-10 毫秒的淡化可防止爆音
  4. 壓縮動態範圍 — UI 音效應具有一致的音量
  5. 匯出為 WAV(適用於原生應用)或 OGG/MP3(適用於網頁,每個音效低於 50KB)
  6. 在目標喇叭上測試 — 手機喇叭會衰減低於 200Hz 的頻率

Web Audio API:程式化音效

對於網頁應用程式,以程式化方式產生音效完全消除了對音訊檔案的需求。更小的套件、即時可用性。

class UISound {
  private ctx: AudioContext | null = null;

  private getContext(): AudioContext {
    if (!this.ctx) {
      this.ctx = new AudioContext();
    }
    return this.ctx;
  }

  /** 明亮的上升確認音 */
  confirm(): void {
    const ctx = this.getContext();
    const osc = ctx.createOscillator();
    const gain = ctx.createGain();

    osc.connect(gain);
    gain.connect(ctx.destination);

    osc.type = 'sine';
    osc.frequency.setValueAtTime(600, ctx.currentTime);
    osc.frequency.linearRampToValueAtTime(900, ctx.currentTime + 0.15);

    gain.gain.setValueAtTime(0.15, ctx.currentTime);
    gain.gain.exponentialRampToValueAtTime(0.001, ctx.currentTime + 0.2);

    osc.start(ctx.currentTime);
    osc.stop(ctx.currentTime + 0.2);
  }

  /** 低沉下降的錯誤音 */
  error(): void {
    const ctx = this.getContext();
    const osc = ctx.createOscillator();
    const gain = ctx.createGain();

    osc.connect(gain);
    gain.connect(ctx.destination);

    osc.type = 'triangle';
    osc.frequency.setValueAtTime(400, ctx.currentTime);
    osc.frequency.linearRampToValueAtTime(200, ctx.currentTime + 0.3);

    gain.gain.setValueAtTime(0.12, ctx.currentTime);
    gain.gain.exponentialRampToValueAtTime(0.001, ctx.currentTime + 0.35);

    osc.start(ctx.currentTime);
    osc.stop(ctx.currentTime + 0.35);
  }

  /** 用於切換和選擇的微弱點擊聲 */
  click(): void {
    const ctx = this.getContext();
    const osc = ctx.createOscillator();
    const gain = ctx.createGain();

    osc.connect(gain);
    gain.connect(ctx.destination);

    osc.type = 'square';
    osc.frequency.setValueAtTime(800, ctx.currentTime);

    gain.gain.setValueAtTime(0.08, ctx.currentTime);
    gain.gain.exponentialRampToValueAtTime(0.001, ctx.currentTime + 0.05);

    osc.start(ctx.currentTime);
    osc.stop(ctx.currentTime + 0.05);
  }

  /** 三音通知旋律 */
  notify(): void {
    const ctx = this.getContext();
    const notes = [523, 659, 784]; // C5, E5, G5

    notes.forEach((freq, i) => {
      const osc = ctx.createOscillator();
      const gain = ctx.createGain();
      osc.connect(gain);
      gain.connect(ctx.destination);

      osc.type = 'sine';
      osc.frequency.setValueAtTime(freq, ctx.currentTime);

      const start = ctx.currentTime + i * 0.12;
      gain.gain.setValueAtTime(0, start);
      gain.gain.linearRampToValueAtTime(0.12, start + 0.02);
      gain.gain.exponentialRampToValueAtTime(0.001, start + 0.15);

      osc.start(start);
      osc.stop(start + 0.15);
    });
  }
}

// 使用方式
const sound = new UISound();
document.querySelector('#submit')?.addEventListener('click', () => sound.confirm());

觸覺-音訊配對(行動裝置)

在行動裝置上,觸覺和音訊應作為一個整體來設計。觸覺先到達(即時的物理回饋),然後聲音到達(確認和特性)。

配對指南

互動觸覺聲音時序
點按按鈕輕微撞擊短促點擊同時
切換開關中度撞擊清脆喀嚓觸覺超前聲音 10 毫秒
下拉重新整理拖曳時選擇滴答聲;完成時通知微弱的拉伸聲;確認鈴聲觸覺領先 20 毫秒
滑動刪除臨界點重擊空洞颼颼聲觸覺在提交點
長按剛性連續振動低沉上升嗡嗡聲觸覺與聲音同時開始
成功成功模式(三重敲擊)上升琶音對齊節拍

iOS 實作

import UIKit
import AVFoundation

class FeedbackManager {
    static let shared = FeedbackManager()

    private let lightImpact = UIImpactFeedbackGenerator(style: .light)
    private let mediumImpact = UIImpactFeedbackGenerator(style: .medium)
    private let heavyImpact = UIImpactFeedbackGenerator(style: .heavy)
    private let notificationFeedback = UINotificationFeedbackGenerator()

    func tapConfirm() {
        lightImpact.impactOccurred()
        SoundPlayer.play(.confirm)
    }

    func errorShake() {
        notificationFeedback.notificationOccurred(.error)
        SoundPlayer.play(.error)
    }

    func deleteCommit() {
        heavyImpact.impactOccurred()
        SoundPlayer.play(.delete)
    }
}

令人滿意聲音的心理學

為什麼有些 UI 聲音感覺「對」,而其他的感覺「廉價」:

令人滿意的聲音特性

特性為什麼有效範例
音高上升表示進展、樂觀、完成確認音向上走
短衰減感覺反應靈敏且可控任天堂選單音效
和聲豐富度感覺有機且溫暖Slack 的「敲門」聲
一致音量感覺專業且可預測Apple 系統音效
節奏對齊感覺有目的且經過設計Duolingo 的連續記錄計數器

惱人的聲音特性

特性為什麼令人煩躁避免
無變化的重複人類會習慣,然後感到煩躁每天 100 次完全相同的聲音
相對於情境太大聲打斷專注力

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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