android-architecture▌
new-silvermoon/awesome-android-agent-skills · updated Apr 8, 2026
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When designing or refactoring an Android application, adhere to the Guide to App Architecture and Clean Architecture principles.
Android Modern Architecture & Modularization
Instructions
When designing or refactoring an Android application, adhere to the Guide to App Architecture and Clean Architecture principles.
1. High-Level Layers
Structure the application into three primary layers. Dependencies must strictly flow inwards (or downwards) to the core logic.
- UI Layer (Presentation):
- Responsibility: Displaying data and handling user interactions.
- Components: Activities, Fragments, Composables, ViewModels.
- Dependencies: Depends on the Domain Layer (or Data Layer if simple). Never depends on the Data Layer implementation details directly.
- Domain Layer (Business Logic) [Optional but Recommended]:
- Responsibility: Encapsulating complex business rules and reuse.
- Components: Use Cases (e.g.,
GetLatestNewsUseCase), Domain Models (pure Kotlin data classes). - Pure Kotlin: Must NOT contain any Android framework dependencies (no
android.*imports). - Dependencies: Depends on Repository Interfaces.
- Data Layer:
- Responsibility: Managing application data (fetching, caching, saving).
- Components: Repositories (implementations), Data Sources (Retrofit APIs, Room DAOs).
- Dependencies: Depends only on external sources and libraries.
2. Dependency Injection with Hilt
Use Hilt for all dependency injection.
- @HiltAndroidApp: Annotate the
Applicationclass. - @AndroidEntryPoint: Annotate Activities and Fragments.
- @HiltViewModel: Annotate ViewModels; use standard
constructorinjection. - Modules:
- Use
@Moduleand@InstallIn(SingletonComponent::class)for app-wide singletons (e.g., Network, Database). - Use
@Bindsin an abstract class to bind interface implementations (cleaner than@Provides).
- Use
3. Modularization Strategy
For production apps, use a multi-module strategy to improve build times and separation of concerns.
- :app: The main entry point, connects features.
- :core:model: Shared domain models (Pure Kotlin).
- :core:data: Repositories, Data Sources, Database, Network.
- :core:domain: Use Cases and Repository Interfaces.
- :core:ui: Shared Composables, Theme, Resources.
- :feature:[name]: Standalone feature modules containing their own UI and ViewModels. Depends on
:core:domainand:core:ui.
4. Checklist for implementation
- Ensure
Domainlayer has no Android dependencies. - Repositories should default to main-safe suspend functions (use
Dispatchers.IOinternally if needed). - ViewModels should interact with the UI layer via
StateFlow(seeandroid-viewmodelskill).
How to use android-architecture on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add android-architecture
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches android-architecture from GitHub repository new-silvermoon/awesome-android-agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate android-architecture. Access the skill through slash commands (e.g., /android-architecture) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★69 reviews- ★★★★★Carlos Martinez· Dec 28, 2024
We added android-architecture from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sophia Gonzalez· Dec 20, 2024
Useful defaults in android-architecture — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Carlos Thompson· Dec 16, 2024
android-architecture has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Dhruvi Jain· Dec 8, 2024
Useful defaults in android-architecture — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Oshnikdeep· Nov 27, 2024
android-architecture is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Noah Jain· Nov 19, 2024
Solid pick for teams standardizing on skills: android-architecture is focused, and the summary matches what you get after install.
- ★★★★★Noah Johnson· Nov 15, 2024
android-architecture reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Nia Bansal· Nov 11, 2024
android-architecture is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 7, 2024
Registry listing for android-architecture matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kofi Perez· Nov 7, 2024
android-architecture fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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