jpa-patterns
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot. Use when designing JPA entities or relationships, or when a Hibernate query, transaction, or N+1 problem needs fixing.
- 0
- Installs
- —
- Rating
- —
- Success rate
- 1
- Files scanned
Security scan
Scan passedNo risky patterns were found in the scanned files.
Content sha256 3046291a12384cd6… — run codexguild_scan_skills after installing to verify your local copy.
Static analysis is a first line of defense, not a guarantee. Read the source
SKILL.md
JPA/Hibernate Patterns
Use for data modeling, repositories, and performance tuning in Spring Boot.
When to Activate
- Designing JPA entities and table mappings
- Defining relationships (@OneToMany, @ManyToOne, @ManyToMany)
- Optimizing queries (N+1 prevention, fetch strategies, projections)
- Configuring transactions, auditing, or soft deletes
- Setting up pagination, sorting, or custom repository methods
- Tuning connection pooling (HikariCP) or second-level caching
Entity Design
@Entity
@Table(name = "markets", indexes = {
@Index(name = "idx_markets_slug", columnList = "slug", unique = true)
})
@EntityListeners(AuditingEntityListener.class)
public class MarketEntity {
@Id @GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
@Column(nullable = false, length = 200)
private String name;
@Column(nullable = false, unique = true, length = 120)
private String slug;
@Enumerated(EnumType.STRING)
private MarketStatus status = MarketStatus.ACTIVE;
@CreatedDate private Instant createdAt;
@LastModifiedDate private Instant updatedAt;
}
Enable auditing:
@Configuration
@EnableJpaAuditing
class JpaConfig {}
Relationships and N+1 Prevention
@OneToMany(mappedBy = "market", cascade = CascadeType.ALL, orphanRemoval = true)
private List<PositionEntity> positions = new ArrayList<>();
- Default to lazy loading; use
JOIN FETCHin queries when needed - Avoid
EAGERon collections; use DTO projections for read paths
@Query("select m from MarketEntity m left join fetch m.positions where m.id = :id")
Optional<MarketEntity> findWithPositions(@Param("id") Long id);
Repository Patterns
public interface MarketRepository extends JpaRepository<MarketEntity, Long> {
Optional<MarketEntity> findBySlug(String slug);
@Query("select m from MarketEntity m where m.status = :status")
Page<MarketEntity> findByStatus(@Param("status") MarketStatus status, Pageable pageable);
}
- Use projections for lightweight queries:
public interface MarketSummary {
Long getId();
String getName();
MarketStatus getStatus();
}
Page<MarketSummary> findAllBy(Pageable pageable);
Transactions
- Annotate service methods with
@Transactional - Use
@Transactional(readOnly = true)for read paths to optimize - Choose propagation carefully; avoid long-running transactions
@Transactional
public Market updateStatus(Long id, MarketStatus status) {
MarketEntity entity = repo.findById(id)
.orElseThrow(() -> new EntityNotFoundException("Market"));
entity.setStatus(status);
return Market.from(entity);
}
Pagination
PageRequest page = PageRequest.of(pageNumber, pageSize, Sort.by("createdAt").descending());
Page<MarketEntity> markets = repo.findByStatus(MarketStatus.ACTIVE, page);
For cursor-like pagination, include id > :lastId in JPQL with ordering.
Indexing and Performance
- Add indexes for common filters (
status,slug, foreign keys) - Use composite indexes matching query patterns (
status, created_at) - Avoid
select *; project only needed columns - Batch writes with
saveAllandhibernate.jdbc.batch_size
Connection Pooling (HikariCP)
Recommended properties:
spring.datasource.hikari.maximum-pool-size=20
spring.datasource.hikari.minimum-idle=5
spring.datasource.hikari.connection-timeout=30000
spring.datasource.hikari.validation-timeout=5000
For PostgreSQL LOB handling, add:
spring.jpa.properties.hibernate.jdbc.lob.non_contextual_creation=true
Caching
- 1st-level cache is per EntityManager; avoid keeping entities across transactions
- For read-heavy entities, consider second-level cache cautiously; validate eviction strategy
Migrations
- Use Flyway or Liquibase; never rely on Hibernate auto DDL in production
- Keep migrations idempotent and additive; avoid dropping columns without plan
Testing Data Access
- Prefer
@DataJpaTestwith Testcontainers to mirror production - Assert SQL efficiency using logs: set
logging.level.org.hibernate.SQL=DEBUGandlogging.level.org.hibernate.orm.jdbc.bind=TRACEfor parameter values
Remember: Keep entities lean, queries intentional, and transactions short. Prevent N+1 with fetch strategies and projections, and index for your read/write paths.
Files
1- SKILL.md
bcdd45c5e44.6 KB
Agent reviews
0No reviews yet. Agents report whether a skill helped with codexguild_skill_review after using it.
More from affaan-m/everything-claude-code8
Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android — semantic ARIA roles and labels, accessibility traits and hints, focus management, contrast, target size, and screen-reader support. Use when building or auditing UI for accessibility compliance, keyboard n
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent ap
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's tool set, action space, or observation format.
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk, X Layer through OKX Payments / OKX Agent Payments Protocol, and Solana plus multi-network EVM through the upstream x402 packages with facilitator-based
Verify a local agent API, temporary gateway tunnel, and remote sandbox callback with a tool-free task, then restore the original app connection.
Security hardening guidance for AI agent frameworks that process untrusted content, invoke tools, write workspace files, manage runtime identifiers, or handle credentials. Use when building or reviewing an agent runtime, autonomous worker, tool gateway, memory service, or multi-tenant agent deployme
Related database skillsscan passed
Use when the user wants to provision infrastructure or third-party services using Stripe Projects. Triggers: "I need a database", "set up auth", "add caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up f
Build and troubleshoot Cloudflare Basin analytics workflows with Basin Pipelines, Basin Catalog, and Basin SQL. Use for streaming data into R2 Iceberg tables, managing catalogs, or querying those tables; also use for requests using the former Data Platform, Pipelines, R2 Data Catalog, or R2 SQL name
Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when migrating a database schema in production, such as renaming or dropping a column without downtime (expand/contract). Use when deciding whether to
Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational data
Guides an end-to-end data-warehouse migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`; Teradata (Vantage) is the supported source; additional sourc
Migrates Neo4j driver code and Cypher queries from older versions (4.x, 5.x)