claude

aidlc

AIDLC Phase 1 (Inception) + Phase 2 (Construction) opt-in extensions for awslabs/aidlc-workflows. Inception covers workspace detection, adaptive-depth requirements analysis, user stories, and workflow planning. Construction covers component design, code generation, TDD-for-agentic test strategy, risk discovery, and phase quality gates.

22 on GitHubby aws-samplesv0.5.0-preview.1Apache-2.0updated 29 days agoaidlc
/

Plugin aidlc from marketplace oh-my-aidlcops in aws-samples/sample-oh-my-aidlcops. Commands read from the repo's manifest — 28 days ago.

This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.

What it installs

Skills (12)

  • code-generation

    승인된 design.md를 기반으로 스캐폴딩·인터페이스·데이터 모델·구현 코드를 단계별로 생성하고 모든 변경을 사람 승인 gate에 제출한다. 템플릿 기반 생성·롤백 스냅샷·계약 위반 감지로 안전성을 확보하며 auto-merge는 금지된다.

  • component-design

    Inception 아티팩트(requirements, user-stories, workflow-plan)를 입력으로 받아 agentic 시스템의 컴포넌트 경계·인터페이스 계약·데이터 모델을 설계하고 `.omao/plans/construction/design.md`를 생성한다. Agent·Tool·Memory·Gateway 경계를 명확히 나누고 후속 code-generation·test-strategy skill의 단일 진실원 역할을 한다.

  • quality-gates

    AIDLC 각 phase 종료 시점에 필수 gate 체크리스트를 강제한다. Inception gate는 요구사항·사용자 스토리·워크플로우 계획 서명을, Construction gate는 설계·코드·테스트 전수 통과와 risk-discovery PASS를, Operations gate는 continuous-eval 24시간 green과 cost-governance budget OK를 요구한다. 미통과 시 `.omao/state/gates/<phase>.json`에 blocked 상태를 기록하고 다음 phase 진입을 차단한다.

  • risk-discovery

    Construction 단계 실행 직전, Inception 아티팩트와 설계 문서를 교차 분석하여 12개 카테고리 기반 위험 체크포인트를 탐지한다. 비즈니스 연속성·보안·외부 통합·데이터 일관성·비용·성능·규제·가용성·장애 전파 반경·운영 복잡도·의존성 취약점·롤백 가능성을 각각 PASS/WARN/BLOCK으로 판정하고 BLOCK 항목은 다음 phase 진입을 차단한다.

  • test-strategy

    Agentic 시스템을 위한 TDD 전략을 수립한다. LLM 클라이언트 mock(VCR-style), golden dataset 기반 eval(최소 5건), hypothesis 기반 property-based test로 비결정성을 제어한다. `.omao/plans/construction/test-plan.md`를 산출하며 code-generation과 병렬 실행 가능하다.

  • requirements-analysis

    Adaptive-depth requirements analysis for AIDLC Inception. Simple features produce a 1-paragraph brief; complex features produce structured REQ-001/REQ-002 functional and non-functional requirements with acceptance criteria and traceability to user stories.

  • structured-intake

    AIDLC Inception 시작 시 자유 형식 발화 대신 구조화된 템플릿으로 프로젝트 정보를 수집한다. project-info 템플릿과 requirements 템플릿을 순차 생성하여 후속 workspace-detection·requirements-analysis·user-stories skill이 소비할 단일 진실원을 제공한다.

  • user-stories

    Conditionally generate user stories in As-a/I-want/So-that format only when changes are user-facing. Skips story generation for pure infrastructure or internal refactor work. Produces stories with acceptance criteria linked back to REQ-IDs.

  • workflow-planning

    Strategic workflow planning for AIDLC Phase 1 close-out. Chooses sequential / parallel-units / iterative execution mode via a decision tree, maps stories to units, and defines checkpoint gates. Produces workflow-plan.md as the hand-off artifact to the aidlc plugin construction phase.

  • workspace-detection

    Detect whether the workspace is greenfield (new project) or brownfield (existing codebase). For brownfield, trigger reverse-engineering to recover implicit requirements. Produces a workspace-report.md with detected stack, entry points, and recommended inception path.

  • ontology-wiki

    생성 전(pre-generation) grounding 레이어. 온톨로지 엔티티(Spec/ADR/Deployment/Agent/Skill/Incident/Budget/Risk)를 작성하기 전에 지식 그래프를 질의해 기존 정의·enum·전례·결정 이유를 확인함으로써 drift를 소스에서 차단한다. adr-0001-graphify-knowledge-wiki 결정에 따라 Graphify(MIT)를 런타임 질의 substrate로 사용하며, Graphify 미가용 시 raw 스키마/docs 읽기로 graceful degradation 한다

  • wiki

Hooks (4)

  • SessionStart

    bash "${CLAUDE_PLUGIN_ROOT}/hooks/session-start-ontology.sh"

  • PreToolUse

    python3 "${CLAUDE_PLUGIN_ROOT}/hooks/enforce.py"

  • Stop

    bash "${CLAUDE_PLUGIN_ROOT}/hooks/stop-gate.sh"

  • StopFailure

    bash "${CLAUDE_PLUGIN_ROOT}/hooks/stop-gate.sh"

View source on GitHub aws-samples.github.io

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