java-coding-standards▌
affaan-m/everything-claude-code · updated Jun 2, 2026
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Coding standards for readable, maintainable Java 17+ in Spring Boot services.
- ›Covers naming conventions (PascalCase for classes, camelCase for methods, UPPER_SNAKE_CASE for constants), immutability patterns with records and final fields, and Optional usage with map/flatMap
- ›Establishes best practices for streams, exception handling with domain-specific exceptions, and type-safe generics
- ›Includes project structure guidance (Maven/Gradle layout), formatting rules, and code smells to avo
Java Coding Standards
Standards for readable, maintainable Java (17+) code in Spring Boot services.
When to Activate
- Writing or reviewing Java code in Spring Boot projects
- Enforcing naming, immutability, or exception handling conventions
- Working with records, sealed classes, or pattern matching (Java 17+)
- Reviewing use of Optional, streams, or generics
- Structuring packages and project layout
Core Principles
- Prefer clarity over cleverness
- Immutable by default; minimize shared mutable state
- Fail fast with meaningful exceptions
- Consistent naming and package structure
Naming
// PASS: Classes/Records: PascalCase
public class MarketService {}
public record Money(BigDecimal amount, Currency currency) {}
// PASS: Methods/fields: camelCase
private final MarketRepository marketRepository;
public Market findBySlug(String slug) {}
// PASS: Constants: UPPER_SNAKE_CASE
private static final int MAX_PAGE_SIZE = 100;
Immutability
// PASS: Favor records and final fields
public record MarketDto(Long id, String name, MarketStatus status) {}
public class Market {
private final Long id;
private final String name;
// getters only, no setters
}
Optional Usage
// PASS: Return Optional from find* methods
Optional<Market> market = marketRepository.findBySlug(slug);
// PASS: Map/flatMap instead of get()
return market
.map(MarketResponse::from)
.orElseThrow(() -> new EntityNotFoundException("Market not found"));
Streams Best Practices
// PASS: Use streams for transformations, keep pipelines short
List<String> names = markets.stream()
.map(Market::name)
.filter(Objects::nonNull)
.toList();
// FAIL: Avoid complex nested streams; prefer loops for clarity
Exceptions
- Use unchecked exceptions for domain errors; wrap technical exceptions with context
- Create domain-specific exceptions (e.g.,
MarketNotFoundException) - Avoid broad
catch (Exception ex)unless rethrowing/logging centrally
throw new MarketNotFoundException(slug);
Generics and Type Safety
- Avoid raw types; declare generic parameters
- Prefer bounded generics for reusable utilities
public <T extends Identifiable> Map<Long, T> indexById(Collection<T> items) { ... }
Project Structure (Maven/Gradle)
src/main/java/com/example/app/
config/
controller/
service/
repository/
domain/
dto/
util/
src/main/resources/
application.yml
src/test/java/... (mirrors main)
Formatting and Style
- Use 2 or 4 spaces consistently (project standard)
- One public top-level type per file
- Keep methods short and focused; extract helpers
- Order members: constants, fields, constructors, public methods, protected, private
Code Smells to Avoid
- Long parameter lists → use DTO/builders
- Deep nesting → early returns
- Magic numbers → named constants
- Static mutable state → prefer dependency injection
- Silent catch blocks → log and act or rethrow
Logging
private static final Logger log = LoggerFactory.getLogger(MarketService.class);
log.info("fetch_market slug={}", slug);
log.error("failed_fetch_market slug={}", slug, ex);
Null Handling
- Accept
@Nullableonly when unavoidable; otherwise use@NonNull - Use Bean Validation (
@NotNull,@NotBlank) on inputs
Testing Expectations
- JUnit 5 + AssertJ for fluent assertions
- Mockito for mocking; avoid partial mocks where possible
- Favor deterministic tests; no hidden sleeps
Remember: Keep code intentional, typed, and observable. Optimize for maintainability over micro-optimizations unless proven necessary.
How to use java-coding-standards 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 java-coding-standards
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches java-coding-standards from GitHub repository affaan-m/everything-claude-code 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 java-coding-standards. Access the skill through slash commands (e.g., /java-coding-standards) 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▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★51 reviews- ★★★★★Yuki Ramirez· Dec 20, 2024
Registry listing for java-coding-standards matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Min Khan· Dec 12, 2024
Useful defaults in java-coding-standards — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Camila Gupta· Dec 8, 2024
We added java-coding-standards from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kiara Gonzalez· Nov 27, 2024
java-coding-standards fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Yash Thakker· Nov 23, 2024
Solid pick for teams standardizing on skills: java-coding-standards is focused, and the summary matches what you get after install.
- ★★★★★Zaid Rahman· Nov 11, 2024
Keeps context tight: java-coding-standards is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Min Zhang· Nov 3, 2024
I recommend java-coding-standards for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Maya Khan· Oct 22, 2024
Keeps context tight: java-coding-standards is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kiara Khan· Oct 18, 2024
java-coding-standards has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Dhruvi Jain· Oct 14, 2024
java-coding-standards is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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