Simple Order Service

A minimal Spring Boot 3.x reference implementation demonstrating Agentic Engineering principles with clear architectural constraints and AI-friendly documentation.

Project Intent

This project exists as a teaching tool and blueprint for agentic systems—showing how to structure a Spring Boot application so that AI agents can understand and extend it reliably. It prioritizes clarity and constraint-driven development over feature completeness.

The service provides a simple REST API for querying order status, deliberately minimal to keep focus on architecture and coding discipline.

Architecture Overview

Framework & Stack

• Java 21 with Spring Boot 3.x
• Maven build system
• In-memory DAO (no external persistence)
• JUnit 5 for testing
• REST API style

Architectural Pattern

HTTP Request
    ↓
OrderController (HTTP concerns only)
    ↓
OrderService (business logic)
    ↓
OrderDao (data access stub)

Core Principles

• Layered architecture with strict separation of concerns
• Constructor injection only (no field injection)
• Controllers are thin (no business logic)
• Service layer owns all business rules
• No direct coupling between layers

Design Principles & Constraints

Must Never Change Casually

• Constructor Injection Only – Field injection defeats dependency management and testability
• Thin Controllers – All business logic must live in services. Controllers handle HTTP concerns only
• Single Responsibility Per Layer – Respect the controller → service → DAO boundary
• Fail Fast – Validate inputs immediately; throw meaningful exceptions; never swallow errors
• No Utility Classes – Avoid static methods and god objects; use composition instead
• Clear Naming – Prefer explicit, long names over clever abbreviations

What This Project Is NOT

• ❌ Not production-ready – Uses in-memory storage; no real database
• ❌ Not a feature factory – Intentionally minimal API to maintain clarity
• ❌ Not a microservices template – Single service only; focuses on internals, not orchestration
• ❌ Not a full-stack example – No frontend, no DevOps, no cloud deployment
• ❌ Not an authorization reference – No authentication/RBAC examples
• ❌ Not a persistence guide – DAO is a stub; not intended as JPA/Hibernate template

Directory Structure

src/main/java/com/example/agentic/
├── Application.java              # Spring Boot entry point
├── controller/
│   └── OrderController.java      # HTTP layer (GET /orders/{id})
├── service/
│   └── OrderService.java         # Business logic layer
├── dao/
│   └── OrderDao.java             # Data access stub
├── dto/                          # Request/response models (placeholder)
├── exception/                    # Custom exceptions (placeholder)
└── model/                        # Domain models (placeholder)

src/test/java/com/example/agentic/
└── service/
    ├── OrderServiceTest.java     # Service layer tests
    └── InvoiceServiceTest.java   # Example test file

.claude/skills/                   # AI agent skill definitions
├── api-design/
├── create-rest-api/
├── dao-access/
├── documentation/
├── service-logic/
├── test-generation/
└── validation/

.github/agents/                   # Agent configurations
├── code-reviewer.agent.md
├── readme-specialist.agent.md
└── subagents/
    └── documentation-writer.agent.md

agents.md                         # Master governance file for all development

API Design

Current Endpoint

GET /orders/{id}

• Purpose: Retrieve the status of an order by ID
• Status Code: 200 OK
• Response: Plain string (e.g., "CREATED")
• Current Behavior: Returns hardcoded "CREATED" status (stub implementation)

⚠️ Design Debt: This endpoint should return a structured DTO with timestamp and full order details. See Error Handling Strategy for missing validation and error responses.

API Design Principles

All API changes must comply with these rules (from agents.md):

• Use resource-oriented URLs (nouns, not verbs)
• Use appropriate HTTP methods (GET, POST, PUT, DELETE)
• Return meaningful HTTP status codes
• Keep request/response models simple
• Never leak internal implementation details via APIs

Coding Standards

JavaScript-Agnostic Guidelines

These constraints apply universally (enforced by agents):

Code Organization

• Constructor injection only
• Controllers must be thin (no business logic)
• Business logic must live in services
• Prefer composition over inheritance
• Avoid static state and utility classes

Code Quality

• Methods should be small and intention-revealing
• Prefer explicit types and clear naming over brevity
• No unnecessary abstractions
• Fail fast on invalid input
• Throw meaningful exceptions with clear messages
• Do not swallow exceptions

Testing

• Write tests for all service-layer logic
• Tests should be behavior-focused, not implementation-focused
• Avoid excessive mocking
• Prefer readable tests over clever tests
• Test names should describe behavior clearly

Security

• Never hardcode secrets or credentials
• Validate all external inputs
• Assume all inputs are untrusted
• Avoid reflection and dynamic execution
• Call out potential security risks explicitly

Error Handling Strategy

Current state: Incomplete – No validation, exception handling, or error responses defined.

Gaps Identified:

• ❌ No HTTP status codes (should use 400, 404, 500, etc.)
• ❌ No validation for order IDs (negative, zero, non-existent)
• ❌ No structured error responses
• ❌ No exception hierarchy defined
• ❌ No error logging strategy

Expected Pattern (from agents.md):

• Fail fast on invalid input
• Throw meaningful exceptions with clear messages
• Do not swallow exceptions
• Separate error handling from business logic
• Errors should be understandable to a human reader

Skills Available in This Project

AI agents use these skill definitions to perform consistent, high-quality work:

Each skill file contains detailed procedures, inputs, outputs, and governing rules.

Agents & Automation

This project includes AI agent definitions to automate and constrain development tasks:

Available Agents

Code Reviewer (.github/agents/code-reviewer.agent.md)

• Reviews Java code for quality, security, and best practices
• Identifies code smells and potential issues
• Checks for proper error handling and logging
• Mandatory handoff to documentation-writer when gaps are found

README Specialist (.github/agents/readme-specialist.agent.md)

• Creates and improves README.md files
• Ensures documentation reflects current project state
• Documents architectural intent and non-goals
• Maintains consistency and scannability

Available Subagents

Documentation Writer (.github/agents/subagents/documentation-writer.agent.md)

• Triggered by code-reviewer when documentation gaps are found
• Creates API specifications, error handling strategies, and data models
• Ensures all architectural decisions are documented

Agent Configuration

Agents are configured via YAML frontmatter in their .agent.md files and respect the governing rules in agents.md. They operate with restricted tool access (read, edit, search, agent invocation) and cannot modify code files—only documentation.

Working Agreement for AI Agents & Humans

For All Contributors:

• If requirements are unclear, ask clarifying questions
• Do not guess business rules
• Propose changes before implementing them (discuss first)
• Explain trade-offs and assumptions
• Optimize for readability and maintainability over speed

Specific Constraints for AI Agents:

• Respect the architecture – Never bypass layering rules or use field injection
• Use skills consistently – All API work uses api-design skill; all tests use test-generation skill
• Document your work – Architectural decisions must be recorded
• Hand off when needed – Code reviewers must trigger documentation handoffs when gaps exist
• Follow agents.md as law – This is your source of truth for development practices
• No casual refactoring – Changes to core constraints (like constructor injection) require explicit approval
• Fail safely – Always create documentation for error scenarios; never assume error handling is trivial

Getting Started

Prerequisites

• Java 21+
• Maven 3.9+

Build & Run

# Build the project
mvn clean package

# Run tests
mvn test

# Start the service
mvn spring-boot:run

The service listens on http://localhost:8080

Test the API

# Get order status
curl http://localhost:8080/orders/1

# Expected response (current stub):
CREATED

Testing

Current Test Coverage

• OrderServiceTest – Tests happy path (returns "CREATED" status)
• InvoiceServiceTest – Placeholder test file

Test Structure

Tests mirror the main package structure:

src/test/java/com/example/agentic/
└── service/
    ├── OrderServiceTest.java
    └── InvoiceServiceTest.java

Testing Principles

From agents.md:

• Write tests for all service-layer logic
• Tests should be behavior-focused, not implementation-focused
• Avoid excessive mocking
• Prefer readable tests over clever tests
• Test names should describe behavior clearly

Current Gaps:

• ❌ No error scenario testing
• ❌ No validation testing
• ❌ No controller layer tests
• ❌ No DAO layer tests

Rules for Humans and AI Agents

Rules For Code Changes

1. Constructor Injection is Mandatory

   • All dependencies must be injected via constructor
   • Field injection is forbidden
   • Reason: Enables testability, immutability, and clear dependency graphs

2. Controllers Are Thin

   • Controllers handle HTTP concerns only (routing, status codes, serialization)
   • All business logic lives in services
   • Reason: Separation of concerns, easier testing, cleaner code

3. Service Layer Owns Business Logic

   • No business decisions in controllers or DAOs
   • Services orchestrate DAOs and apply rules
   • Reason: Centralized, testable business logic; easier to understand and modify

4. Fail Fast

   • Validate inputs immediately upon entry
   • Throw exceptions with clear messages
   • Never swallow exceptions silently
   • Reason: Easier debugging, clearer error messages, faster problem resolution

5. No Static Utility Classes

   • Avoid static methods and static fields
   • Use composition and dependency injection instead
   • Reason: Testability, state management, dependency visibility

6. Naming Matters

   • Prefer clarity over brevity (e.g., findOrderStatus vs. findOS)
   • Method names should describe intent (e.g., validateOrderId not check)
   • Reason: Code is read 10x more than it's written; reduce cognitive load

Rules for AI Agents

1. Respect Architectural Boundaries

   • Do not put business logic in controllers
   • Do not bypass layers with direct DAO access from controllers
   • Do not use field injection or static state

2. Use Skills Consistently

   • When creating APIs, use the api-design skill
   • When writing tests, use the test-generation skill
   • When defining DAOs, use the dao-access skill
   • Reference the skill files before implementing

3. Document Your Work

   • Add JavaDoc to public classes and methods
   • Record architectural decisions and trade-offs
   • Update this README if you change project intent or constraints

4. Hand Off Appropriately

   • Code reviewers: Trigger documentation-writer handoff when gaps exist
   • Never skip mandatory handoffs
   • Wait for documentation draft before completing code review

5. Ask Before Changing Core Constraints

   • Do not modify constructor injection requirement
   • Do not add field injection as an exception
   • Do not create utility classes
   • Changes to these require explicit approval

6. Assume All Inputs Are Untrusted

   • Always validate external input (HTTP params, request bodies)
   • Use the validation skill for complex validation logic
   • Return 400 Bad Request for invalid input, not 500 Internal Server Error

Configuration

Spring Boot Configuration

# src/main/resources/application.yml
spring:
  application:
    name: simple-agentic

Contributing

See agents.md for the complete governance model and working agreements.

For documentation contributions, see .github/agents/readme-specialist.agent.md.

Project Governance

This project is governed by agents.md, which defines:

• Coding standards and architectural rules
• API design principles
• Testing and error handling expectations
• Security guidelines
• Working agreements for humans and AI agents

All development must align with agents.md. If you find a contradiction between this README and agents.md, agents.md takes precedence.

License

This project is provided as-is for educational and reference purposes.

Last Updated: January 28, 2026
Project Type: Reference Implementation (Agentic Engineering)