Persistence layer patterns for Spring Data JPA repositories, entities, queries, and advanced features.
Works with
Create repository interfaces extending JpaRepository with derived queries, custom @Query methods, and automatic CRUD operations
Configure entity relationships (one-to-one, one-to-many, many-to-many) with appropriate cascade types and fetch strategies
Implement pagination, sorting, database auditing with timestamps and user tracking, and transaction management
Optimize performance
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionspring-data-jpaExecute the skills CLI command in your project's root directory to begin installation:
Fetches spring-data-jpa from giuseppe-trisciuoglio/developer-kit and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate spring-data-jpa. Access via /spring-data-jpa in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Provides patterns for Spring Data JPA repositories, entity relationships, queries, pagination, auditing, and transactions.
Creating repositories with CRUD operations, entity relationships, @Query annotations, pagination, auditing, or UUID primary keys.
To implement a repository interface:
Extend the appropriate repository interface:
@Repository
public interface UserRepository extends JpaRepository<User, Long> {
// Custom methods defined here
}
Use derived queries for simple conditions:
Optional<User> findByEmail(String email);
List<User> findByStatusOrderByCreatedDateDesc(String status);
Implement custom queries with @Query:
@Query("SELECT u FROM User u WHERE u.status = :status")
List<User> findActiveUsers(@Param("status") String status);
Define entities with proper annotations:
@Entity
@Table(name = "users")
public class User {
@Id
@GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
@Column(nullable = false, length = 100)
private String email;
}
Configure relationships using appropriate cascade types:
@OneToMany(mappedBy = "user", cascade = CascadeType.ALL, orphanRemoval = true)
private List<Order> orders = new ArrayList<>();
Validation: Test cascade behavior with a small dataset before applying to production data. Verify delete operations don't cascade unexpectedly.
Set up database auditing:
@CreatedDate
@Column(nullable = false, updatable = false)
private LocalDateTime createdDate;
@Query for complex queries@Modifying for update/delete operations@Transactional(readOnly = true)1. Verify entity configuration:
2. Optimize query performance:
EXPLAIN ANALYZE on queries against large tables@EntityGraph to prevent N+1 queries3. Validate pagination:
@Repository
public interface ProductRepository extends JpaRepository<Product, Long> {
// Derived query
List<Product> findByCategory(String category);
// Custom query
@Query("SELECT p FROM Product p WHERE p.price > :minPrice")
List<Product> findExpensiveProducts(@Param("minPrice") BigDecimal minPrice);
}
@Service
public class ProductService {
private final ProductRepository repository;
public Page<Product> getProducts(int page, int size) {
Pageable pageable = PageRequest.of(page, size, Sort.by("name").ascending());
return repository.findAll(pageable);
}
}
@Entity
@EntityListeners(AuditingEntityListener.class)
public class Order {
@Id
@GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
@CreatedDate
@Column(nullable = false, updatable = false)
private LocalDateTime createdDate;
@LastModifiedDate
private LocalDateTime lastModifiedDate;
@CreatedBy
@Column(nullable = false, updatable = false)
private String createdBy;
}
final modifiers@Value for DTOs@Id and @GeneratedValue annotations@Table and @Column annotations@EntityGraph to avoid N+1 query problemsFor comprehensive examples, detailed patterns, and advanced configurations, see:
@EntityGraph or JOIN FETCH in queries.CascadeType.REMOVE on large collections as it can cause performance issues.EAGER fetch type for collections; it can cause excessive database queries.@Transactional(readOnly = true) for read operations to enable optimizations.Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
spring-data-jpa has been reliable in day-to-day use. Documentation quality is above average for community skills.
spring-data-jpa is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: spring-data-jpa is the kind of skill you can hand to a new teammate without a long onboarding doc.
spring-data-jpa reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in spring-data-jpa — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: spring-data-jpa is focused, and the summary matches what you get after install.
spring-data-jpa has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: spring-data-jpa is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: spring-data-jpa is focused, and the summary matches what you get after install.
spring-data-jpa reduced setup friction for our internal harness; good balance of opinion and flexibility.
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