unit-test-json-serialization▌
giuseppe-trisciuoglio/developer-kit · updated Apr 8, 2026
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Unit testing JSON serialization and deserialization with Spring's @JsonTest and Jackson.
- ›Covers serialization/deserialization of POJOs, custom serializers/deserializers, field name mappings with @JsonProperty , and null handling using JacksonTester for type-safe assertions
- ›Includes patterns for testing nested objects, lists, date/time formatting, and polymorphic types with @JsonTypeInfo
- ›Provides Maven and Gradle setup, best practices for avoiding circular references and null inclusio
Unit Testing JSON Serialization with @JsonTest
Overview
Provides patterns for unit testing JSON serialization and deserialization using Spring's @JsonTest and Jackson. Covers POJO mapping, custom serializers, field name mappings, nested objects, date/time formatting, and polymorphic types.
When to Use
- Testing JSON serialization/deserialization of DTOs
- Verifying custom Jackson serializers/deserializers
- Validating
@JsonProperty,@JsonIgnore, and field name mappings - Testing date/time format handling (LocalDateTime, Date)
- Testing null handling and missing fields
- Testing polymorphic type deserialization
Instructions
- Annotate test class with
@JsonTest→ Enables JacksonTester auto-configuration - Autowire JacksonTester for target type → Provides type-safe JSON assertions
- Test serialization → Call
json.write(object)and assert JSON paths withextractingJsonPath* - Test deserialization → Call
json.parse(json)orjson.parseObject(json)and assert object state - Validate round-trip → Serialize, then deserialize, verify same data (if object is properly comparable)
- Test edge cases → Null values, missing fields, empty collections, invalid JSON
- Add validation checkpoints: After each assertion, verify the test fails meaningfully with wrong data
Examples
Maven Setup
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-json</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
Gradle Setup
dependencies {
implementation("org.springframework.boot:spring-boot-starter-json")
testImplementation("org.springframework.boot:spring-boot-starter-test")
}
Basic Serialization and Deserialization
@JsonTest
class UserDtoJsonTest {
@Autowired
private JacksonTester<UserDto> json;
@Test
void shouldSerializeUserToJson() throws Exception {
UserDto user = new UserDto(1L, "Alice", "[email protected]", 25);
JsonContent<UserDto> result = json.write(user);
result
.extractingJsonPathNumberValue("$.id").isEqualTo(1)
.extractingJsonPathStringValue("$.name").isEqualTo("Alice")
.extractingJsonPathStringValue("$.email").isEqualTo("[email protected]")
.extractingJsonPathNumberValue("$.age").isEqualTo(25);
}
@Test
void shouldDeserializeJsonToUser() throws Exception {
String json_content = "{\"id\":1,\"name\":\"Alice\",\"email\":\"[email protected]\",\"age\":25}";
UserDto user = json.parse(json_content).getObject();
assertThat(user.getId()).isEqualTo(1L);
assertThat(user.getName()).isEqualTo("Alice");
assertThat(user.getEmail()).isEqualTo("[email protected]");
assertThat(user.getAge()).isEqualTo(25);
}
@Test
void shouldHandleNullFields() throws Exception {
String json_content = "{\"id\":1,\"name\":null,\"email\":\"[email protected]\"}";
UserDto user = json.parse(json_content).getObject();
assertThat(user.getName()).isNull();
}
}
Custom JSON Properties
public class Order {
@JsonProperty("order_id")
private Long id;
@JsonProperty("total_amount")
private BigDecimal amount;
@JsonIgnore
private String internalNote;
}
@JsonTest
class OrderJsonTest {
@Autowired
private JacksonTester<Order> json;
@Test
void shouldMapJsonPropertyNames() throws Exception {
String json_content = "{\"order_id\":123,\"total_amount\":99.99}";
Order order = json.parse(json_content).getObject();
assertThat(order.getId()).isEqualTo(123L);
assertThat(order.getAmount()).isEqualByComparingTo(new BigDecimal("99.99"));
}
@Test
void shouldIgnoreJsonIgnoreFields() throws Exception {
Order order = new Order(123L, new BigDecimal("99.99"));
order.setInternalNote("Secret");
assertThat(json.write(order).json).doesNotContain("internalNote");
}
}
Nested Objects
public class Product {
private Long id;
private String name;
private Category category;
private List<Review> reviews;
}
@JsonTest
class ProductJsonTest {
@Autowired
How to use unit-test-json-serialization 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 unit-test-json-serialization
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches unit-test-json-serialization from GitHub repository giuseppe-trisciuoglio/developer-kit 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 unit-test-json-serialization. Access the skill through slash commands (e.g., /unit-test-json-serialization) 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
4.7★★★★★63 reviews- ★★★★★Yuki Menon· Dec 28, 2024
Keeps context tight: unit-test-json-serialization is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yusuf Thomas· Dec 20, 2024
We added unit-test-json-serialization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Daniel Garcia· Dec 16, 2024
unit-test-json-serialization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Yusuf Anderson· Dec 8, 2024
Registry listing for unit-test-json-serialization matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ganesh Mohane· Dec 4, 2024
Solid pick for teams standardizing on skills: unit-test-json-serialization is focused, and the summary matches what you get after install.
- ★★★★★Daniel Harris· Dec 4, 2024
unit-test-json-serialization reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kofi Liu· Nov 27, 2024
Useful defaults in unit-test-json-serialization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakshi Patil· Nov 23, 2024
We added unit-test-json-serialization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Daniel Bhatia· Nov 23, 2024
I recommend unit-test-json-serialization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yash Thakker· Nov 19, 2024
unit-test-json-serialization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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