spring-data-neo4j

giuseppe-trisciuoglio/developer-kit · updated Apr 8, 2026

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$npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill spring-data-neo4j
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summary

Spring Data Neo4j integration for graph databases with repositories, Cypher queries, and reactive operations.

  • Three abstraction levels: Neo4j Client (low-level), Neo4j Template (medium-level), and Neo4j Repositories (high-level query derivation)
  • Supports both imperative Neo4jRepository and reactive ReactiveNeo4jRepository patterns; do not mix both in the same application
  • Entity mapping with @Node and @Relationship annotations, supporting business keys or generated IDs with immutable
skill.md

Spring Data Neo4j Integration Patterns

Overview

Provides Spring Data Neo4j integration patterns for Spring Boot applications. Covers node entity mapping with @Node and @Relationship, repository configuration (imperative and reactive), custom Cypher queries with @Query, and integration testing with embedded Neo4j databases.

When to Use

Use this skill when working with:

  • Graph databases and Neo4j integration in Spring Boot
  • Node entities, relationships, and Cypher queries
  • Spring Data Neo4j repositories (imperative or reactive)
  • Neo4j testing with embedded databases

Instructions

1. Set Up Spring Data Neo4j

Add the dependency:

Maven:

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-neo4j</artifactId>
</dependency>

Gradle:

implementation 'org.springframework.boot:spring-boot-starter-data-neo4j'

Configure connection in application.properties:

spring.neo4j.uri=bolt://localhost:7687
spring.neo4j.authentication.username=neo4j
spring.neo4j.authentication.password=secret

Configure Cypher-DSL dialect (recommended):

@Configuration
public class Neo4jConfig {
    @Bean
    Configuration cypherDslConfiguration() {
        return Configuration.newConfig()
            .withDialect(Dialect.NEO4J_5).build();
    }
}

Validation Checkpoint: Run MATCH (n) RETURN count(n) via cypher-shell to verify the connection works before proceeding.

2. Define Node Entities

  1. Use @Node annotation to mark entity classes
  2. Choose ID strategy:
    • Business key as @Id (immutable, natural identifier)
    • Generated @Id @GeneratedValue (Neo4j internal ID)
  3. Define relationships with @Relationship annotation
  4. Keep entities immutable with final fields
  5. Use @Property for custom property names

Validation Checkpoint: If entity save fails, check for constraint violations—duplicate IDs violate uniqueness constraints.

3. Create Repositories

  1. Extend repository interface:
    • Neo4jRepository<Entity, ID> for imperative operations
    • ReactiveNeo4jRepository<Entity, ID> for reactive operations
  2. Use query derivation for simple queries
  3. Apply @Query annotation for complex Cypher queries
  4. Use $paramName syntax for parameters

Validation Checkpoint: Test repository with findAll() first—if empty, verify the Neo4j instance is running and credentials are correct.

4. Test Your Implementation

  1. Use @DataNeo4jTest for repository testing with test slicing
  2. Set up Neo4j Harness with embedded database and fixtures
  3. Provide test data via withFixture() Cypher queries
  4. Clean up test data between tests

Validation Checkpoint: If tests fail with "Connection refused", ensure the embedded Neo4j started successfully in @BeforeAll.

Basic Entity Mapping

Node Entity with Business Key

@Node("Movie")
public class MovieEntity {

    @Id
    private final String title;  // Business key as ID

    @Property("tagline")
    private final String description;

    private final Integer year;

    @Relationship(type = "ACTED_IN", direction = Direction.INCOMING)
    private List<Roles> actorsAndRoles = new ArrayList<>();

    @Relationship(type = "DIRECTED", direction = Direction.INCOMING)
    private List<PersonEntity> directors = new ArrayList<>();

    public MovieEntity(String title, String description, Integer year) {
        this.title = title;
        this.description = description;
        this.year = year;
    }
}

Node Entity with Generated ID

@Node("Movie")
public class MovieEntity {

    @Id @GeneratedValue
    private Long id;

    private final String title;

    @Property("tagline")
    private final String description;

    public MovieEntity(String title, String description) {
        this.id = null;  // Never set manually
        this.title = title;
        this.description = description;
    }

    // Wither method for immutability with generated IDs
    public MovieEntity withId(Long id) {
        if (this.id != null && this.id.equals(id)) {
            return this;
        } else {
            MovieEntity newObject = new MovieEntity(this.title, this.description);
            newObject.id = id;
            return newObject;
        }
    }
}

Repository Patterns

Basic Repository Interface

@Repository
public interface MovieRepository extends Neo4jRepository<MovieEntity, String> {

    // Query derivation from method name
    MovieEntity findOneByTitle(String title);

    List<MovieEntity> findAllByYear(Integer year);

    List<MovieEntity> findByYearBetween(Integer startYear, Integer endYear);
}

Reactive Repository

@Repository
public interface MovieRepository extends ReactiveNeo4jRepository<MovieEntity, String> {

    Mono<MovieEntity> findOneByTitle(String title);

    Flux<MovieEntity> findAllByYear(Integer year);
}

Imperative vs Reactive:

  • Use Neo4jRepository for blocking, imperative operations
  • Use ReactiveNeo4jRepository for non-blocking, reactive operations
  • Do not mix imperative and reactive in the same application
  • Reactive requires Neo4j 4+ on the database side

Custom Queries with @Query

@Repository
public interface AuthorRepository extends Neo4jRepository<Author, Long> {

    @Query("MATCH (b:Book)-[:WRITTEN_BY]->(a:Author) " +
           "WHERE a.name = $name AND b.year > $year " +
           "RETURN b")
    List<Book> 
how to use spring-data-neo4j

How to use spring-data-neo4j on Cursor

AI-first code editor with Composer

1

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 spring-data-neo4j
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill spring-data-neo4j

The skills CLI fetches spring-data-neo4j from GitHub repository giuseppe-trisciuoglio/developer-kit and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/spring-data-neo4j

Reload or restart Cursor to activate spring-data-neo4j. Access the skill through slash commands (e.g., /spring-data-neo4j) 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.

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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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.658 reviews
  • Maya Agarwal· Dec 16, 2024

    spring-data-neo4j reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ira Flores· Dec 16, 2024

    spring-data-neo4j has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Smith· Dec 16, 2024

    spring-data-neo4j fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Jin Gill· Dec 8, 2024

    We added spring-data-neo4j from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Amina Martin· Nov 27, 2024

    spring-data-neo4j reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Amina Sharma· Nov 11, 2024

    Registry listing for spring-data-neo4j matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Jin Shah· Nov 7, 2024

    We added spring-data-neo4j from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ishan Taylor· Nov 7, 2024

    Solid pick for teams standardizing on skills: spring-data-neo4j is focused, and the summary matches what you get after install.

  • Aisha Ramirez· Nov 7, 2024

    I recommend spring-data-neo4j for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Amina Thompson· Oct 26, 2024

    Keeps context tight: spring-data-neo4j is the kind of skill you can hand to a new teammate without a long onboarding doc.

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