What problem does it solve? Before implementing any change in a Spring Boot application, an AI agent needs reliable project context: the tech stack, domain entities, repositories, services, mappers, DTOs, and existing REST endpoints. Gathering this manually by reading files is slow and error-prone. This Skill collects that context systematically through the Amplicode Spring MCP server and produces a structured exploration report. ## Core Features & Use Cases - Guided exploration workflow: A six-step process that predicts involved components, selects only relevant exploration paths, executes MCP tool calls via a subagent, and synthesizes a structured report. - JPA and Spring Data JDBC support: Detects the persistence stack and routes entity analysis through the appropriate reference guides, including DDD aggregate boundary analysis. - Implicit assumption detection: Surfaces unstated expectations (authentication, pagination style, validation, error handling) so they can be validated before implementation. - Use Case: Before adding a paginated endpoint for customer orders, run the exploration to learn the Spring Boot version, confirm OrderRepository exists, check for existing OrderDto and OrderMapper, and review current endpoint conventions. ## Quick Start Ask the agent to explore this Spring Boot project and give me an overview of its tech stack, domain entities, and REST endpoints before we start the task.
