SDD Artifact Rollout

Implements the 5-phase rollout methodology for Specification-Driven Development artifact frameworks, enabling teams to create AI-ready specifications that drive code generation.

When to Use This Skill

新規プロジェクト

• SDD/スペック駆動開発の導入
• ドメイン用語集（Glossary）やユビキタス言語の作成
• Bounded Context Mapの設計
• 形式的受け入れ基準付きUser Storiesの構造化
• ドメインモデル（Aggregate, Entity, Value Object）の構築
• ADR（Architecture Decision Record）の確立

既存プロジェクト

• 既存コードベースの包括的文書化
• レガシープロジェクトへのSDD準拠アーティファクト追加
• コードからGlossary/Domain Modelのリバースエンジニアリング
• 既存APIからOpenAPI仕様書の生成
• 技術的負債・設計判断の事後記録（ADR）
• 文書化ギャップの診断と優先順位付け

Quick Start: Context Gathering

Before proceeding, gather these inputs from the user:

1. Domain: What is the target domain? (e.g., order management, billing)
2. Team: How many people? What roles? (PO, Tech Lead, Dev, QA, DevOps)
3. Timeline: Available weeks? (Standard: 12 weeks for full rollout)
4. Regulatory: Any compliance requirements? (affects Phase 5 depth)
5. Existing Artifacts: Any glossary, domain model, or specs already exist?
6. Project Type: NEW project or EXISTING codebase?

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既存プロジェクト向けガイド

既存コードベースにSDD準拠のアーティファクトを導入する場合は、以下のガイドを参照：

ガイド	用途
ギャップ診断	現状分析、何が欠けているか診断、優先順位付け
リバースエンジニアリング	コード→Glossary、コード→Domain Model、API→OpenAPI抽出
暗黙知の明示化	インタビュー手順、PR履歴分析、事後ADR作成
段階的移行ロードマップ	MVP定義、移行計画、日常業務への組み込み

既存プロジェクトでの推奨フロー

1. ギャップ診断（何が欠けているか）
   ↓
2. 優先順位付け（どこから着手するか）
   ↓
3. MVP Level 1 作成（Vision, Glossary 15用語, Context Map）
   ↓
4. リバースエンジニアリング（コードから抽出）
   ↓
5. 暗黙知収集（インタビュー、事後ADR）
   ↓
6. 段階的に Level 2, 3 へ拡充

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新規プロジェクト向け: Phase Overview (12-Week Standard)

Phase	Weeks	Focus	Key Deliverables
1	1-2	Foundation	Domain Vision, Glossary v0.1, Context Map
2	3-5	Requirements	User Stories, Formal ACs, Feature Breakdown
3	6-8	Conceptual Design	Domain Model, Events, Service Specs
4	8-10	Data & API	Data Models, OpenAPI Specs, Code Skeleton
5	10-12	Operations	ADRs, Validation Automation, CI/CD

Execution Flow

Phase 1: Foundation (Weeks 1-2)

Goal: Establish ubiquitous language and AI context foundation.

Deliverables:

1. Domain Vision Statement (1-2 pages)
2. Core Glossary v0.1 (20-30 terms in YAML)
3. Bounded Context Map (3-5 contexts)

AI Usage: Heavy (glossary generation, context refinement)

For detailed templates and procedures, see phase-1-foundation.md.

Phase 2: Requirements (Weeks 3-5)

Goal: Structure user stories for AI code generation compatibility.

Deliverables:

1. User Stories v1 (5-10 per sprint)
2. Acceptance Criteria (formal + natural language)
3. Feature Breakdown & Dependencies

AI Usage: Medium (story generation, AC refinement)

For detailed templates and procedures, see phase-2-requirements.md.

Phase 3: Conceptual Design (Weeks 6-8)

Goal: Develop domain models with explicit invariants.

Deliverables:

1. Domain Model (Aggregates, Entities, Value Objects)
2. Domain Events & Event Flow
3. Service Specifications (Application/Domain)

AI Usage: Medium-High (code skeleton generation)

For detailed templates and procedures, see phase-3-domain-design.md.

Phase 4: Data & Implementation Design (Weeks 8-10)

Goal: Define data schemas and external interfaces.

Deliverables:

1. Logical & Physical Data Models
2. OpenAPI Specifications
3. Implementation Code Skeleton

AI Usage: Heavy (code generation, schema inference)

For detailed templates and procedures, see phase-4-data-api.md.

Phase 5: Integration & Operations (Weeks 10-12)

Goal: Complete artifact lifecycle management with CI/CD integration.

Deliverables:

1. ADRs for all major decisions
2. Validation & Quality Check Automation
3. CI/CD integration, deployment pipeline
4. Artifact versioning & change management

AI Usage: Light (validation logic generation)

For detailed templates and procedures, see phase-5-ops-automation.md.

Validation at Each Phase

Before advancing to the next phase, verify:

• All deliverables created and reviewed
• Glossary terms used consistently across artifacts
• Referential integrity checked (all referenced concepts defined)
• Stakeholder approval obtained

For validation scripts and detailed checks, see validation.md.

Templates

AI prompt templates for each phase are provided in templates.md.

Checklists

Phase-by-phase implementation checklists are in checklist.md.

Success Factors

1. Early Commitment: Team understands why documentation matters for AI
2. Tool Simplicity: Start with Git + Markdown + YAML
3. Iterative Refinement: Don't aim for perfect; iterate
4. AI Usage Clarity: Define which stages use AI generation
5. Feedback Loop: Implementation feedback flows back to artifacts

Required Roles

Role	Responsibilities
Domain Expert / PO	Glossary, Business Rules, Story validation
Architect / Tech Lead	Context Map, ADR, Framework design
Senior Developer	Domain Model, code generation
Mid Developer	Feature implementation, story completion
QA / Tester	AC validation, test case generation
DevOps	CI/CD, artifact versioning, validation automation

Recommended Repository Structure

project-repo/
├── domain/
│   ├── vision.md
│   └── glossary.yaml
├── architecture/
│   ├── context-map.md
│   └── strategic-rules.md
├── requirements/
│   ├── user-stories.md
│   └── features/
├── domain-design/
│   ├── domain-model.ts
│   └── aggregates/
├── data-model/
│   ├── schema.sql
│   └── migrations/
├── api-specs/
│   └── openapi.yaml
├── adr/
│   └── ADR-001-*.md
├── ai/
│   └── prompt-templates.yaml
└── scripts/
    └── validate-artifacts.sh

Adaptation Guidelines

新規プロジェクト

• Startup (small team): Focus on Phase 1-2, minimal Phase 5
• Growth-stage: Full 5-phase rollout over 12 weeks
• Enterprise: Add regulatory artifacts, extend Phase 5

既存プロジェクト

• レガシー（文書なし）: ギャップ診断から開始、MVP Level 1を最優先
• 部分的に文書あり: ギャップ診断で欠けている部分を特定、優先順位付けして補完
• リファクタリング予定: リバースエンジニアリングでDomain Model抽出を優先
• 新メンバー頻繁: Glossary, Domain Vision, Context Mapを最優先

Next Steps

After gathering context, proceed to Phase 1:

1. Read phase-1-foundation.md
2. Create Domain Vision Statement using template
3. Generate initial Glossary with AI assistance
4. Draft Bounded Context Map
5. Validate and get approval before Phase 2