How does this skill integrate into the development workflow?

It functions as a mid-stage design tool that takes NFR requirements as input and generates detailed design plans and logical component maps before infrastructure or code is created.

Does this skill require manual user input?

Yes, it generates specific questions in markdown files when pattern decisions require human architectural judgment, ensuring the user remains in control of key design choices.

What does this skill mean by NFR?

NFR stands for Non-Functional Requirements, which include system attributes like performance, scalability, reliability, and security that define the quality of the software.

Which architectural patterns does it support?

The skill focuses on resilience (e.g., circuit breakers), scalability (e.g., horizontal scaling), performance (e.g., caching), and security patterns.

NFR Architecture & Design

Name: NFR Architecture & Design
Author: yamatatsu

byyamatatsu

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클라우드 인프라

Incorporate non-functional requirements like scalability, resilience, and security into software unit designs using proven architectural patterns.

The NFR Architecture & Design skill is a specialized component of the AI-DLC framework designed to bridge the gap between requirement gathering and system implementation. It automatically analyzes NFR requirements for specific software units and proposes standardized design patterns for resilience, performance, and security. By identifying necessary logical components such as message queues, caching layers, and load balancers, the skill ensures that architectural decisions are documented and aligned with industry best practices before the coding phase begins.

주요 기능

01Automated NFR pattern analysis for performance and scalability

02Integrated audit logging and state management within the AI-DLC workflow

03Context-aware interactive decision-making via markdown-based question flows

04Structured artifact generation for architectural documentation

050 GitHub stars

06Identification of critical logical components like caches and queues

사용 사례

01Designing high-availability microservices with resilience patterns

02Architecting secure and performant API units within a structured SDLC

03Standardizing non-functional design patterns across distributed engineering teams

주요 기능

01Automated NFR pattern analysis for performance and scalability

02Integrated audit logging and state management within the AI-DLC workflow

03Context-aware interactive decision-making via markdown-based question flows

04Structured artifact generation for architectural documentation

050 GitHub stars

06Identification of critical logical components like caches and queues

사용 사례

01Designing high-availability microservices with resilience patterns

02Architecting secure and performant API units within a structured SDLC

03Standardizing non-functional design patterns across distributed engineering teams