High-level component identification and service layer design. Use when identifying main functional components, defining component interfaces, designing service orchestration, or establishing component dependencies and communication patterns.
Generate comprehensive build and test instructions after code generation is complete. Covers build steps, unit tests, integration tests, performance tests, contract tests, security tests, and e2e tests. Use when all code generation is done and the project needs build/test documentation.
Generate code for a unit of work with a two-part approach - planning then generation. Use when implementing features, writing application code, creating tests, or generating deployment artifacts based on approved designs.
AI-DLC CONSTRUCTION phase - Detailed design, implementation, and testing. Use when generating code, designing business logic, defining NFR requirements, creating infrastructure design, or building and testing. Handles functional design, NFR requirements, NFR design, infrastructure design, code generation, and…
Design detailed business logic, domain models, and business rules for a unit of work. Technology-agnostic design focused purely on business functions. Use when designing complex business logic, data models, or validation rules.
AI-DLC INCEPTION phase - Planning and architecture workflow. Use when starting a new software development request, analyzing requirements, creating user stories, planning workflow, or designing application architecture. Handles workspace detection, reverse engineering, requirements analysis, user stories, workflow…
Map logical software components to actual infrastructure services (AWS, Azure, GCP, on-premise). Use when designing deployment architecture, selecting cloud services, or planning infrastructure for a unit of work.
Determine non-functional requirements (NFR) and design NFR patterns for a unit. Covers scalability, performance, availability, security, tech stack selection, resilience patterns, and logical components. Use when addressing performance, security, scalability, or tech stack decisions.
Gather, analyze, and document software requirements with adaptive depth. Use when clarifying what to build, analyzing user needs, or creating requirements documents. Handles intent analysis, clarifying questions, and requirements generation.
Analyze an existing codebase to generate comprehensive architecture, code structure, API, and dependency documentation. Use when working with a brownfield project that needs understanding before making changes.
Resume an existing AI-DLC workflow from where it was last paused. Use when returning to continue work on an in-progress AI-DLC project, or when aidlc-state.md already exists.
Create user stories and personas from requirements using INVEST criteria. Use when converting business requirements into user-centered stories with acceptance criteria, defining user personas, or establishing shared understanding across teams.
A local connector to the Saga Event Space API, a service containing information about event spaces, hotels, and reception venues in Saga Prefecture, Japan.