Spring Data Neo4j integration for graph databases with repositories, Cypher queries, and reactive operations.
Works with
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionspring-data-neo4jExecute the skills CLI command in your project's root directory to begin installation:
Fetches spring-data-neo4j 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-neo4j. Access via /spring-data-neo4j 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.
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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 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.
Use this skill when working with:
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.
@Node annotation to mark entity classes@Id (immutable, natural identifier)@Id @GeneratedValue (Neo4j internal ID)@Relationship annotation@Property for custom property namesValidation Checkpoint: If entity save fails, check for constraint violations—duplicate IDs violate uniqueness constraints.
Neo4jRepository<Entity, ID> for imperative operationsReactiveNeo4jRepository<Entity, ID> for reactive operations@Query annotation for complex Cypher queries$paramName syntax for parametersValidation Checkpoint: Test repository with
findAll()first—if empty, verify the Neo4j instance is running and credentials are correct.
@DataNeo4jTest for repository testing with test slicingwithFixture() Cypher queriesValidation Checkpoint: If tests fail with "Connection refused", ensure the embedded Neo4j started successfully in
@BeforeAll.
@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("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
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);
}
@Repository
public interface MovieRepository extends ReactiveNeo4jRepository<MovieEntity, String> {
Mono<MovieEntity> findOneByTitle(String title);
Flux<MovieEntity> findAllByYear(Integer year);
}
Imperative vs Reactive:
Neo4jRepository for blocking, imperative operationsReactiveNeo4jRepository for non-blocking, reactive operations@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> ✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
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4.6★★★★★58 reviews- MMaya Agarwal★★★★★Dec 16, 2024
spring-data-neo4j reduced setup friction for our internal harness; good balance of opinion and flexibility.
- IIra Flores★★★★★Dec 16, 2024
spring-data-neo4j has been reliable in day-to-day use. Documentation quality is above average for community skills.
- IIshan Smith★★★★★Dec 16, 2024
spring-data-neo4j fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- JJin Gill★★★★★Dec 8, 2024
We added spring-data-neo4j from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- AAmina Martin★★★★★Nov 27, 2024
spring-data-neo4j reduced setup friction for our internal harness; good balance of opinion and flexibility.
- AAmina Sharma★★★★★Nov 11, 2024
Registry listing for spring-data-neo4j matched our evaluation — installs cleanly and behaves as described in the markdown.
- JJin Shah★★★★★Nov 7, 2024
We added spring-data-neo4j from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- IIshan 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.
- AAisha Ramirez★★★★★Nov 7, 2024
I recommend spring-data-neo4j for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- AAmina 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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