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curiositech/windags-skills

App Store 與 Google Play 自動化提交工具,整合 Fastlane、螢幕截圖自動化、中繼資料管理及 TestFlight/內部測試。

windags-skills 是什麼?

此技能專為需要自動化 App Store 與 Google Play 應用程式提交流程的開發者設計。它全面整合 Fastlane,涵蓋螢幕截圖生成、中繼資料管理、程式碼簽署以及 TestFlight/內部測試軌道等關鍵環節。其核心優勢在於透過結構化的決策點與品質閘門,引導使用者選擇最佳發布策略(如階段性上線 vs 全面上線)、憑證更新時機與提交類型。技能文件明確列出了常見失敗模式的症狀、診斷與解決方案(如憑證不匹配、審查被拒、超時問題),並提供了一個完整的 React Native 應用程式設定範例,清晰展示了從 init 到自動化提交的步驟,可將提交時間從 45 分鐘縮短至 8 分鐘。此技能預設 CI/CD 環境已存在,不處理管線建置、應用程式架構或分析等非關領域。

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

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說明文件

App Store 提交自動化工具

精通透過 Fastlane、螢幕截圖生成、中繼資料管理與審查最佳化,自動化處理 App Store 與 Google Play 提交作業。

決策點

何時使用階段性上線 vs 全面上線

如果是第一個應用程式版本或有重大功能變更:
  └── 使用階段性上線:10% → 50% → 100% 為期 7 天
      └── 在各階段監控當機率與使用者回饋
否則如果為熱修復或次要更新:
  └── 如果是關鍵安全性修復:
      └── 立即全面上線
  否則:
      └── 使用 50% → 100% 為期 2-3 天

憑證更新決策矩陣

情境到期前天數動作
發布憑證< 30 天執行 fastlane match nuke distribution,然後重新產生
開發憑證< 30 天執行 fastlane match nuke development
佈建設定檔< 14 天使用 force_for_new_devices: true 參數執行 match
推播憑證< 30 天在 Apple Developer Portal 重新產生,更新伺服器

提交類型選擇

  ├── iOS:使用 TestFlight 外部群組(最多 10,000 名測試者)
  └── Android:使用內部軌道(最多 100 名測試者)
否則如果需要公開 Beta 測試:
  ├── iOS:使用 TestFlight 公開連結
  └── Android:使用附帶選擇加入 URL 的封閉軌道
否則如果已準備好正式發布:
  ├── 檢查是否滿足所有商店要求(參見品質閘門)
  └── 使用正式發布/發布軌道

失敗模式

Match 憑證不符

  • 症狀:「找不到憑證」或「佈建設定檔與憑證不符」
  • 診斷: Git 儲存庫不同步,或團隊成員手動產生了憑證
  • 修復: 執行 fastlane match nuke,重新產生所有憑證,並提交至 match 儲存庫

App Review 拒絕 - 資訊不足

  • 症狀:「我們需要更多資訊才能審查您的應用程式」
  • 診斷: 缺少示範帳號憑證、聯絡資訊或審查備註
  • 修復: 在 fastlane/metadata/review_information/ 中加入 demo_user.txt、demo_password.txt 和詳細的 notes.txt

大型應用程式建置逾時

  • 症狀: Fastlane 在 build_app 步驟期間逾時
  • 診斷: 應用程式大小 > 2GB 或建置過程複雜
  • 修復: 在 build_app 動作中加入 build_timeout: 7200,啟用增量建置

螢幕截圖生成失敗

  • 症狀: snapshot/screengrab 產生空白或不正確的螢幕截圖
  • 診斷: UI 測試未等待動畫完成,或使用了錯誤的模擬器
  • 修復: 在 UI 測試中加入明確的等待,確認模擬器名稱與 Snapfile 裝置清單相符

中繼資料字元數超過限制

  • 症狀: 上傳失敗,出現「描述太長」錯誤
  • 診斷: 本地化中繼資料超過平台限制(App Store:4000 字元,Play Store:4000 字元)
  • 修復: 在提交前執行 fastlane precheck,將描述修剪至平台限制內

完整範例

**情境:**為一個同時支援 iOS 與 Android 的 React Native 應用程式設定自動化提交

初步評估:

  • 應用程式已有手動提交流程
  • 一個 4 人開發團隊需要共享程式碼簽署
  • 需要階段性上線與螢幕截圖自動化功能

步驟 1:設定決策

# 在專案根目錄
fastlane init
# 選擇選項 4(手動設定)

**遇到決策點:**憑證管理策略

  • **新手選擇:**使用 Xcode 自動簽署(在 CI 中會失敗)
  • **專家選擇:**設定 match 以實現團隊共享憑證

步驟 2:設定 Match

# fastlane/Matchfile
git_url("https://github.com/company/certificates")
storage_mode("git")
type("appstore") # 也支援:development, adhoc

步驟 3:建立 Lane(關鍵決策:Beta vs 正式發布)

# fastlane/Fastfile
desc "TestFlight 提交並增加建置編號"
lane :beta do
  setup_ci if ENV['CI']
  match(type: "appstore", readonly: true)
  
  # 決策:始終增加建置編號,版本號僅在發布時增加
  increment_build_number(build_number: ENV['BUILD_NUMBER'])
  
  build_app(workspace: "ios/MyApp.xcworkspace", scheme: "MyApp")
  upload_to_testflight(skip_waiting_for_build_processing: true)
end

**專家見解:**在 CI 環境中始終使用 skip_waiting_for_build_processing: true 以避免逾時

步驟 4:首次執行前的驗證

  • 執行 fastlane precheck 驗證中繼資料
  • 在單一裝置上進行測試,然後再進行完整的螢幕截圖自動化
  • 確認 CI 環境安裝了正確的 Xcode 版本

**結果:**自動化流程將提交時間從 45 分鐘縮短至 8 分鐘

品質閘門

執行正式發布 Lane 前必須通過的提交前檢查清單:

  • fastlane precheck 執行無警告
  • 所有必要的中繼資料檔案存在於 fastlane/metadata/[locale]/ 中
  • 已為所有必要的裝置尺寸(iPhone 6.9 吋、6.3 吋、iPad 13 吋)產生螢幕截圖
  • 版本號已從上一個發布版本遞增
  • 建置編號是唯一的,且高於 TestFlight 的最新編號
  • 程式碼簽署憑證有效期 > 30 天
  • 如果應用程式需要登入,已在 review_information/ 中提供示範帳號憑證
  • 已設定階段性上線百分比(建議從 10% 開始)
  • 已設定 CI 環境變數:FASTLANE_USER、MATCH_PASSWORD、FASTLANE_SESSION
  • 已完成目標市場的所有本地化作業
  • 應用程式圖示和必要資源已以正確格式提供

不適用範圍

請勿將此技能用於:

  • CI/CD 管線設定 → 請改用 github-actions-pipeline-builder

    • 此技能假設 CI 環境已存在,不會建立工作流程/管線
  • 應用程式架構決策 → 請改用 react-native-architect

    • 此技能處理部署作業,不處理程式碼結構或導航
  • 分析與當機回報 → 請改用 mobile-analytics-crash-reporting-expert

    • 此技能專注於商店提交,不處理發布後監控
  • App Store 最佳化 (ASO) → 請諮詢專屬的 ASO 專家

    • 此技能處理技術性提交,不處理關鍵字最佳化或轉換率
  • 後端 API 開發 → 請改用 api-architect

    • 此技能假設您的應用程式後端已準備好上線

何時應委派:

  • 對於建置設定問題 → react-native-architect
  • 對於從頭開始設定 CI/CD → github-actions-pipeline-builder
  • 對於應用程式效能監控 → mobile-analytics-crash-reporting-expert

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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