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curiositech/windags-skills

擅長 2000 年代音樂視覺化(Milkdrop、AVS、Geiss)及現代 WebGL 實作,專精於 Butterchurn 整合、Web Audio API 的 AnalyserNode FFT 資料、音訊反應式 GLSL 著色器與迷幻生成藝術。

windags-skills 是什麼?

此技能專注於重現 2000 年代傳奇音樂視覺化軟體(如 Milkdrop、AVS、Geiss)的效果,並利用現代 WebGL 和 Web Audio API 技術實現。它支援 Butterchurn 函式庫(WebGL 版 Milkdrop)的整合,能取得 Web Audio API AnalyserNode 的 FFT 頻譜資料,並編寫 GLSL 片段著色器來製作音訊反應式視覺效果。技能也涵蓋即時節奏偵測、預設系統、視覺轉場與全螢幕沉浸式體驗。適用平台包括瀏覽器中的任何 WebGL 環境,並提供完整的整合檢查清單、效能最佳化建議,以及需避免的反模式(如忽略 AudioContext 狀態、線性頻率顯示或缺乏平滑處理)。對於希望打造迷幻、動態音樂視覺體驗的開發者與 AI 代理來說,這是一份實用指南。

相容平台~Claude Code~Codex CLI✓Cursor
npx skills add https://github.com/curiositech/windags-skills/tree/HEAD/skills/2000s-visualization-expert

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說明文件

2000 年代音樂視覺化專家

專精於重現傳奇的 2000 年代音樂視覺化時代——Milkdrop、AVS、Geiss——使用現代 WebGL 與 Web Audio API。

使用時機

✅ 適用於:

  • 實作 Milkdrop 風格的迷幻視覺效果
  • Butterchurn 函式庫整合(WebGL Milkdrop)
  • Web Audio API AnalyserNode 的 FFT/波形擷取
  • 音訊反應式效果的 GLSL 片段著色器
  • 全螢幕沉浸式音樂體驗
  • 即時節奏偵測與音訊分析
  • 預設系統與視覺轉場

❌ 不適用於:

  • 簡單的頻譜長條圖(請使用 Canvas 2D)
  • 靜態音訊波形顯示
  • 影片剪輯或處理
  • 非音訊生成藝術
  • 音訊播放/串流問題(請使用音訊工程師技能)

黃金年代(摘要)

年代關鍵軟體創新
1998-2000Geiss簡單電漿效果,DirectX
2001-2007Milkdrop 1 與 2逐像素方程式,預設系統
2007-2015衰退期串流服務興起
2018-至今ButterchurnWebGL 復興

Milkdrop 的魔力:將簡單效果(模糊、縮放、旋轉、顏色偏移)與音訊反應參數層疊組合。

→ 完整歷史與整合請見 references/butterchurn-guide.md

核心技術

Butterchurn(WebGL Milkdrop)

  • GitHub 星數 1.7k,MIT 授權
  • 與原始 Milkdrop 完全預設相容
  • npm:butterchurn、butterchurn-presets
import butterchurn from 'butterchurn';
const visualizer = butterchurn.createVisualizer(audioContext, canvas, {
  width: window.innerWidth,
  height: window.innerHeight,
  pixelRatio: window.devicePixelRatio || 1,
});
visualizer.connectAudio(audioNode);
visualizer.loadPreset(preset, 2.0);  // 2 秒混合

Web Audio API FFT

const analyser = audioContext.createAnalyser();
analyser.fftSize = 2048;
analyser.smoothingTimeConstant = 0.8;
const frequencyData = new Uint8Array(analyser.frequencyBinCount);
analyser.getByteFrequencyData(frequencyData);

關鍵:FFT 區間是線性的,但聽覺是對數的!請使用對數映射。

→ 頻段擷取請見 references/web-audio-fft.md

GLSL 著色器

將音訊資料以 1D 紋理傳入,使用 uniform 變數表示低音/中音/高音:

uniform float u_bass;
float glow = smoothstep(0.5 - u_bass * 0.3, 0.0, dist);

→ 完整模式請見 references/glsl-shaders.md

應避免的反模式

1. 忽略 AudioContext 狀態

表現:視覺化無聲失敗 錯誤原因:AudioContext 初始為暫停狀態,需使用者互動 修正:點擊時恢復:await audioContext.resume()

2. 線性頻率顯示

表現:低音主導,高音看不見 錯誤原因:FFT 區間是線性的;前 100 個區間可能只有 0-2kHz 修正:使用對數區間映射(程式碼在參考資料中)

3. 缺乏平滑處理

表現:畫面抖動,引發癲癇的視覺效果 錯誤原因:原始 FFT 資料在幀與幀之間充滿雜訊 修正:analyserNode.smoothingTimeConstant = 0.7

4. requestAnimationFrame 未清理

表現:記憶體洩漏,多個渲染迴圈 修正:儲存動畫 ID,並在卸載時呼叫 cancelAnimationFrame

5. 硬編碼畫布尺寸

表現:在 retina 螢幕上模糊,長寬比錯誤 修正:乘以 devicePixelRatio,處理 resize 事件

6. 阻塞主執行緒

表現:音訊卡頓,畫面掉幀 錯誤原因:在 UI 執行緒上進行繁重的著色器編譯 修正:在載入時編譯著色器,而非播放期間

預設推薦

迷幻/致幻:

  • Flexi, martin + geiss - dedicated to the sherwin maxawow
  • Rovastar - Fractopia

流暢/放鬆:

  • Flexi - predator-prey-spirals
  • Geiss - Cosmic Strings 2

高能量:

  • Flexi + Martin - disconnected
  • shifter - tumbling cubes

整合檢查清單

  • 建立 AudioContext 並在使用者互動時恢復
  • 將 AnalyserNode 連接到音訊來源
  • 正確設定畫布尺寸(考量 devicePixelRatio)
  • 使用 requestAnimationFrame 的渲染迴圈
  • 卸載時清理(cancelAnimationFrame)
  • 預設載入並設定混合時間
  • 處理 resize 事件
  • 支援全螢幕,可按 ESC 退出
  • 曲目資訊覆蓋層(z-index 高於畫布)
  • 無操作後隱藏游標

效能提示

  1. 針對舊 GPU 降低紋理比例:textureRatio: 0.5
  2. 若不需要,降低 fftSize:使用 512 或 1024 而非 2048
  3. 對畫布使用 will-change: transform
  4. 在渲染迴圈中避免 DOM 更新
  5. 使用 Chrome DevTools GPU 時間軸進行分析

參考資料

→ references/butterchurn-guide.md - 完整的 Butterchurn 整合指南 → references/web-audio-fft.md - FFT 擷取與頻率分析 → references/glsl-shaders.md - 音訊反應式著色器模式


此技能涵蓋:Butterchurn/Milkdrop | Web Audio FFT | GLSL 著色器 | 全螢幕視覺化 | 音訊反應式藝術

Individual skills in this repo

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

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

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

curiositech/windags-skills

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

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