Communitygithub.com

curiositech/windags-skills

使用 Fastlane 自动化 App Store 和 Google Play 提交,包括截图自动化、元数据管理以及 TestFlight/内部测试。

windags-skills 是什么?

此技能专为自动化移动应用商店提交流程而设计,支持 iOS 和 Android 平台。它基于 Fastlane 构建,能够处理代码签名、元数据管理、截图生成、Staged Rollout 以及 TestFlight/Google Play 控制台发布。该技能不仅提供了详细的决策点,如证书续期矩阵、提交类型选择(内部测试、公开测试、生产发布)和分阶段与全量发布的决策流程,还系统性地总结了常见故障模式及其修复方案,包括 Match 凭据不匹配、应用审核拒绝、构建超时和截图失败等。此外,技能还包含了从零开始配置 Fastlane 的完整实例,以及提交前必须通过的 11 项质量门禁检查。最后,它明确界定了自己的职责范围,避免处理 CI/CD 管道搭建、应用架构或分析等工作,从而确保开发团队能够专注于商店提交的自动化与优化。

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

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

App Store 提交流程自动化专家

精通使用 Fastlane 自动化 App Store 和 Google Play 提交,包括截图生成、元数据管理和审核优化。

决策要点

何时使用分阶段与全量发布

如果是首个应用版本或者主要功能变更:
  └── 使用分阶段发布:10% → 50% → 100%,持续 7 天
      └── 在每个阶段监控崩溃率和用户反馈
否则如果是热修复或小更新:
  └── 如果是关键安全修复:
      └── 立即全量发布
  否则:
      └── 使用 50% → 100%,持续 2-3 天

证书续期决策矩阵

场景到期天数操作
分发证书< 30 天运行 fastlane match nuke distribution,然后重新生成
开发证书< 30 天运行 fastlane match nuke development
配置文件< 14 天使用 force_for_new_devices: true 运行 match
推送证书< 30 天在 Apple Developer Portal 重新生成,更新服务器

提交类型选择

如果需要内部测试:
  ├── iOS:使用 TestFlight 外部组(最多 10,000 名测试人员)
  └── Android:使用内部轨道(最多 100 名测试人员)
否则如果是公开测试:
  ├── iOS:使用 TestFlight 公开链接
  └── Android:使用带有选择加入 URL 的封闭轨道
否则如果是生产就绪:
  ├── 检查是否符合所有商店要求(参见质量门禁)
  └── 使用生产/发布轨道

故障模式

Match 凭据不匹配

  • 症状: “未找到证书”或“配置文件与证书不匹配”
  • 诊断: Git 仓库不同步或团队成员手动生成了证书
  • 修复: 运行 fastlane match nuke,重新生成所有证书,提交到 match 仓库

应用审核被拒 - 信息缺失

  • 症状: “我们需要更多信息来审核您的应用”
  • 诊断: 缺少演示凭据、联系信息或审核说明
  • 修复: 在 fastlane/metadata/review_information/ 中添加 demo_user.txt、demo_password.txt 和详细的 notes.txt

大型应用构建超时

  • 症状: Fastlane 在 build_app 步骤超时
  • 诊断: 应用大小 > 2GB 或构建过程复杂
  • 修复: 在 build_app 操作中添加 build_timeout: 7200,启用增量构建

截图生成失败

  • 症状: snapshot/screengrab 生成空白或不正确的截图
  • 诊断: UI 测试未等待动画完成或使用了错误的模拟器
  • 修复: 在 UI 测试中添加显式等待,验证模拟器名称与 Snapfile 中的设备列表匹配

元数据字符限制超出

  • 症状: 上传失败,报错“描述太长”
  • 诊断: 本地化元数据超出平台限制(App Store:4000 字符,Play Store:4000 字符)
  • 修复: 在提交前运行 fastlane precheck,将描述修剪到平台限制以内

工作示例

场景: 为一个包含 iOS 和 Android 目标的 React Native 应用设置自动提交

初步评估:

  • 应用有现有的手动提交流程
  • 4 人团队需要共享代码签名
  • 要求进行分阶段发布和截图自动化

第一步:设定决策

# 在项目根目录
fastlane init
# 选择选项 4(手动设置)

遇到决策点: 证书管理策略

  • 新手选择: 使用 Xcode 自动签名(在 CI 中会失败)
  • 专家选择: 设置 match 以实现团队范围内的证书共享

第二步:配置 Match

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

第三步:创建通道(关键决策:Beta 与 Production)

# fastlane/Fastfile
desc "TestFlight 提交,构建号自增"
lane :beta do
  setup_ci if ENV['CI']
  match(type: "appstore", readonly: true)
  
  # 决策:始终自增构建号,版本号仅在发布时自增
  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

专家见解: 在 CI 中始终使用 skip_waiting_for_build_processing: true 以避免超时

第四步:首次运行前的验证

  • 运行 fastlane precheck 以验证元数据
  • 在全量截图自动化前,先在单个设备上测试
  • 验证 CI 环境具有正确的 Xcode 版本

结果: 自动化管道将提交流程从 45 分钟缩短至 8 分钟

质量门禁

在运行生产通道之前必须通过的提交前检查清单:

  • fastlane precheck 通过,无警告
  • fastlane/metadata/[locale]/ 目录下存在所有必需的元数据文件
  • 已为所有必需的设备尺寸生成截图(iPhone 6.9", 6.3", iPad 13")
  • 版本号已从上一个发布版本递增
  • 构建号唯一且高于 TestFlight 最新版本
  • 代码签名证书有效期超过 30 天
  • review_information/ 中提供了演示凭据(如果应用需要登录)
  • 已配置分阶段发布百分比(建议从 10% 开始)
  • CI 环境变量已设置:FASTLANE_USER, MATCH_PASSWORD, FASTLANE_SESSION
  • 目标市场的所有本地化工作已完成
  • 应用图标和所需资源以正确格式存在

非职责边界

不要将此技能用于:

  • CI/CD 管道搭建 → 改用 github-actions-pipeline-builder

    • 此技能假设 CI 已存在;不会创建工作流/管道
  • 应用架构决策 → 改用 react-native-architect

    • 此技能处理部署,不涉及代码结构或导航
  • 分析和崩溃报告 → 改用 mobile-analytics-crash-reporting-expert

    • 此技能专注于商店提交,而非发布后的监控
  • 应用商店优化(ASO) → 使用专门的 ASO 专家

    • 此技能处理技术提交流程,而非关键词优化或转化率
  • 后端 API 开发 → 改用 api-architect

    • 此技能假设您的应用后端已为生产环境做好准备

何时委托:

  • 对于构建配置问题 → react-native-architect
  • 对于从头开始搭建 CI/CD → github-actions-pipeline-builder
  • 对于应用性能监控 → 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.

相关技能