
ddd-architecture-evaluator
DDD architecture evaluation and evolution — DDD maturity 5-level model (AdHoc/Aware/Applied/Scaled/Optimized), architecture fitness assessment (business alignment/team fit/tech fit/evolution capability), technical debt quantification with scoring, architecture evolution roadmap (4 phases), and migration risk assessment. Use when user asks about architecture evaluation, 架构评估, DDD maturity, 技术债务, architecture evolution, 架构演进, or needs to assess DDD implementation health.
- Installs
- 135
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/full-stack-skills/ddd-skills --skill ddd-architecture-evaluator- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ddd-architecture-evaluator automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
DDD Architecture Evaluator
Architecture evaluation & evolution — systematically assess DDD health, quantify technical debt, and plan architecture evolution. Supports any project type (Java/Go/Python/TS/.NET) with a structured, repeatable process.
When to read
打开此文档参考流程时可以开始评估。当用户问及架构评估、DDD 成熟度、技术债务量化或架构演进时参考:
- "帮我评估一下项目架构" → 直接开始 Workflow
- "我们的 DDD 做得怎么样" → 从成熟度评估开始
- "技术债务太高了怎么办" → 从技术债务量化开始
- "需要从 MVC 迁移到 DDD" → 从演进路线图开始
Workflow
Step 1: Assess Maturity
→ Run 5-level DDD maturity checklist (L1 → L5)
→ Identify current level vs target level (L3 is sufficient for most projects)
→ Output: Maturity level + per-level pass/fail + key gaps
Step 2: Evaluate Fitness
→ Score 5 dimensions: Business Alignment (25%), Team Fit (25%),
Technology Fit (20%), Evolution Capability (15%), Delivery Efficiency (15%)
→ Calculate weighted fitness score
→ Output: Dimension scores + total fitness + green/yellow/orange/red rating
Step 3: Quantify Debt
→ Structural debt (P0, weight 0.5) — layer violations, circular deps, anemic entities
→ Design debt (P1, weight 0.3) — oversized aggregates, missing VOs/events
→ Testing debt (P2, weight 0.2) — domain unit test coverage
→ Output: Total debt score + health rating (green/mild/moderate/severe)
Step 4: Plan Evolution
→ 4-phase roadmap: Emergency (1-2w) → Short-term (2-4w) →
Mid-term (1-3m) → Long-term (ongoing)
→ Migration risk assessment with Strangler Fig strategy
→ Output: Phased roadmap + risk matrix + next assessment date
Boundary
✅ 擅长处理
| Area | What It Delivers |
|---|---|
| DDD 成熟度评估 | L1-L5 逐级检查清单 + 得分计算 + 关键差距分析 |
| 架构适配度五维评估 | Business / Team / Technology / Evolution / Delivery 加权评分 |
| 技术债务量化 | 结构/设计/测试三类债务 + 加权分数 + 四档健康评级 |
| 架构演进路线图 | 4 阶段演进计划 + 每阶段时间估算 + 优先级排序 |
| 迁移风险评估 | Strangler Fig 渐进迁移方案 + 风险矩阵 + 回退策略 |
| 周期性架构健康检查 | 结构化评估报告 + 改进项追踪 + 下一次评估时间建议 |
⚠️ 需要条件
- 项目有代码可审:项目已运行一段时间,有实际代码库(全新项目建议用
ddd-architecture-selector) - 团队可提供项目背景:需要参考架构文档、代码结构、团队规模等信息
- 明确的评估目标:建议指定评估焦点(整体成熟度 / 特定模块评估 / 迁移可行性)
❌ 不适用 / 超出范围
- 代码级审查 → 使用
ddd-code-reviewer(反模式检测、分层合规检查) - 新项目架构选型 → 使用
ddd-architecture-selector(5 种架构对比决策矩阵) - DDD 入门学习 → 使用
ddd-architecture-awesome(概念速查、充血vs贫血对比) - 架构具体落地实现 → 分别使用
ddd-architecture-layered/onion/hexagonal/clean/cola
Security & 安全说明
本 Skill 是非侵入式分析框架。评估时不访问代码库、不收集项目数据、不上传任何信息。所有评估结果基于用户提供的上下文在当前对话中完成,不存储、不传输至第三方。用户自行决定是否披露项目结构信息。
DDD Maturity 5-Level Model
| Level | Name | Focus | Pass Threshold |
|---|---|---|---|
| L1 | Ad Hoc(初始级) | 3-layer + anemic entities + all logic in Service | ≥ 5/7 |
| L2 | Aware(认知级) | Partial rich model + VOs in use + team awareness | ≥ 3/5 |
| L3 | Applied(实践级) | Aggregate boundaries + Domain zero-deps + rich entities | ≥ 5/7 |
| L4 | Scaled(规模化级) | Multi-BC + CQRS + automated ArchUnit CI | ≥ 5/7 |
| L5 | Optimized(优化级) | Continuous evolution + ES + ADR + debt dashboard | ≥ 5/7 |
完整逐级检查清单见 maturity-levels-detail.md。
Architecture Fitness 5-Dimension Assessment
| Dimension | Weight | Score 1-5 | What to Check |
|---|---|---|---|
| Business Alignment | 25% | 1-5 | Does architecture match business complexity? Over/under-engineered? |
| Team Fit | 25% | 1-5 | Does team understand and follow conventions? Violation rate? |
| Technology Fit | 20% | 1-5 | Does tech stack support the architecture? Friction points? |
| Evolution Capability | 15% | 1-5 | Can new BCs be added? Refactoring cost? Module coupling? |
| Delivery Efficiency | 15% | 1-5 | Feature delivery cycle vs industry baseline? Architecture overhead? |
Total Fitness = BA×0.25 + TF×0.25 + TechF×0.20 + EC×0.15 + DE×0.15
Score interpretation:
≥ 4.0 → 🟢 Excellent
3.0-3.9 → 🟡 Adequate
2.0-2.9 → 🟠 Concerning
< 2.0 → 🔴 Critical
See fitness-assessment-template.md for full scoring rubrics and assessment prompts.
Technical Debt Quantification
Category Breakdown
| Category (Priority) | Weight | Metrics |
|---|---|---|
| Structural Debt (P0) | 0.5 | Layer violation ratio, circular dependency count, anemic entity %, framework leak % |
| Design Debt (P1) | 0.3 | Oversized aggregate ratio, missing domain event ratio, VO missing rate, cross-aggregate refs |
| Testing Debt (P2) | 0.2 | Domain unit test coverage, aggregate root test coverage, integration test coverage |
Calculation
Total Debt = Structural×0.5 + Design×0.3 + Testing×0.2
| Score | Rating | Action |
|---|---|---|
| ≤ 20 | 🟢 Healthy | 无需干预 |
| 21–40 | 🟡 Mild | 定期偿还 |
| 41–60 | 🟠 Moderate | 本季度制定计划 |
| > 60 | 🔴 Severe | 立即启动重构 |
详细方法论和计算示例见 debt-calculation-guide.md。
4-Phase Evolution Roadmap
Traditional 3-Layer → DDD 4-Layer → DDD + Rich Domain → Hexagonal/Clean → Microservices + DDD
| Phase | Duration | Focus | Key Actions |
|---|---|---|---|
| 1. Emergency (止血) | 1-2 weeks | Fix P0 violations | Cut layer violations, remove circular deps, fix cross-aggregate refs |
| 2. Short-term (微重构) | 2-4 weeks | Core domain richness | Rich-fy core aggregates, introduce VOs (Money/Phone/Address), add domain events |
| 3. Mid-term (架构升级) | 1-3 months | Architecture upgrade | Split monolith into BCs, adopt CQRS (L1 start), upgrade pattern as needed |
| 4. Long-term (持续演进) | Ongoing | Continuous evolution | Monthly fitness check, debt dashboard, ADR recording, team DDD training |
Migration Risk Assessment
Pre-Migration Checklist
- ☐ Architecture documented (C4 / ADR)
- ☐ Business complexity assessment done
- ☐ Team DDD knowledge assessed
- ☐ Migration scope defined (full vs incremental)
- ☐ Target architecture agreed (team + stakeholders)
- ☐ Rollback plan established (≤ 4 hours)
Strangler Fig — New features → target arch; old features → keep + gradually replace; core aggregates → migrate first.
Risk Matrix
| Risk Level | Impact | Response |
|---|---|---|
| High | Core business logic | Canary release + automated rollback |
| Medium | Non-core features | Parallel run with traffic mirroring |
| Low | Read-only / queries | Direct switch with performance validation |
See migration-risk-checklist.md for full migration assessment templates.
Gotchas
常见评估陷阱见 references/gotchas.md。
FAQ
| Question | Answer |
|---|---|
| 评估频率? | 推荐季度评估。新功能频繁受阻、债务影响交付、重大业务变更时应触发。 |
| 一次评估要多久? | 小型 1-2h,中型 0.5-1 天,大型 2-3 天。首次较长,后续可复用基线。 |
| 所有项目都需要 Level 5? | 不是。Level 3 对大多数业务系统已足够。Level 4-5 适用于核心金融、交易系统。 |
| 如何度量进步? | 建立基线,每次对比:成熟度变化、债务分数、改进项完成率(目标 ≥ 80%)。 |
| 评估后下一步? | 修复 P0 → 核心域充血 → 架构升级 → 持续演进。每个阶段后快速复审。 |
Keywords
DDD maturity, architecture fitness, technical debt, architecture evolution, migration assessment, Strangler Fig, bounded context, CQRS, Event Sourcing, architecture decision record, ADR, technical debt quantification, 架构评估, 成熟度模型, 技术债务量化, 架构演进, 迁移风险, 架构适配度, 分层合规
References
- maturity/assessment-workflow.md — Maturity assessment preparation, session workflow, and common traps
- maturity/maturity-levels-detail.md — Per-level detailed checklists with scoring
- fitness/scoring-rubric.md — Scoring rubric with context-based calibration
- fitness/fitness-assessment-template.md — 5-dimension scoring rubrics and prompts
- debt/repayment-strategies.md — Debt repayment strategies and prioritization matrix
- debt/debt-calculation-guide.md — Technical debt methodology with examples
- migration/strangler-fig-detailed.md — Detailed Strangler Fig migration planning
- migration/migration-risk-checklist.md — Migration readiness checklist and risk matrix
- evolution-cases.md — Real-world evolution case studies (e-commerce, FinTech, SaaS)
- code-smells-diagnosis.md — Architecture anti-patterns and diagnosis
- migration-path.md — 6-step MVC-to-DDD migration path
- partme-11-ddd-refactoring.md — DDD refactoring case study with enterprise modeling
- gotchas.md — 评估常见陷阱(评分偏差、迁移成本、团队能力等)
FAQ
What does the ddd-architecture-evaluator skill do?
DDD architecture evaluation and evolution — DDD maturity 5-level model (AdHoc/Aware/Applied/Scaled/Optimized), architecture fitness assessment (business alignment/team fit/tech fit/evolution capability), technical debt quantification with scoring, architecture evolution roadmap (4 phases), and migration risk assessment. Use when user asks about architecture evaluation, 架构评估, DDD maturity, 技术债务, architecture evolution, 架构演进, or needs to assess DDD implementation health.
How do I install ddd-architecture-evaluator?
Run npx skills add https://github.com/full-stack-skills/ddd-skills --skill ddd-architecture-evaluator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ddd-architecture-evaluator/ (personal) or .claude/skills/ddd-architecture-evaluator/ (project).
Which AI agents can use ddd-architecture-evaluator?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ddd-architecture-evaluator safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ddd-architecture-evaluator?
It is published by full-stack-skills in full-stack-skills/ddd-skills. It has 135 recorded installs.
More from full-stack-skills/ddd-skills
ddd-code-reviewer
full-stack-skills/ddd-skills
DDD code review and anti-pattern detection — anemia model detection, layered compliance checking, aggregate design review, rich model verification, scoring system (5 dimensions), and ArchUnit automated validation. Use when user asks about code review, 代码审查, DDD review, 架构审查, anti-pattern detection, 反模式检测, or needs to check if code follows DDD.
ddd-api-designer
full-stack-skills/ddd-skills
API design from domain model — CQRS command/query separation, REST API endpoint design, data object conversion chain (PO→DO→DTO→VO), unified response format, OpenAPI/Swagger generation, BFF pattern, API versioning, and security design. Use when user asks about API design, REST API, OpenAPI, BFF, DTO design, 接口设计, or data object conversion.
ddd-architecture-selector
full-stack-skills/ddd-skills
Architecture selection decision guide — help users choose from 5 DDD architectures (Layered/Onion/Hexagonal/Clean/COLA) with decision matrix, team size mapping, domain classification (core/generic/supporting), microservice splitting recommendation, and CQRS level suggestion. Use when user asks about architecture selection, 架构选型, COLA vs 六边形, cleaner architecture vs onion, 微服务拆分, or which architecture to use.
ddd-architecture-doc
full-stack-skills/ddd-skills
DDD architecture documentation generation — C4 model diagrams (Context/Container/Component/Code), ADR (Architecture Decision Records), domain model documentation, API documentation, architecture decision log, and team communication templates. Use when user asks about architecture documentation, 架构文档, ADR, C4 diagram, domain model doc, 架构决策记录, or needs to document DDD architecture for team.
ddd-domain-designer
full-stack-skills/ddd-skills
Open the skill to read its SKILL.md instructions.
ddd-devops-integration
full-stack-skills/ddd-skills
DDD DevOps integration — CI/CD pipeline with ArchUnit automated architecture validation, multi-module build optimization for DDD projects, containerized deployment with Docker/K8s for layered/hexagonal/clean architectures, database migration strategies for domain events, and monitoring domain health. Use when user asks about DevOps, CI/CD, DDD deployment, ArchUnit CI, or needs to automate DDD project builds.
Popular code quality & workflow skills
grill-me
mattpocock/skills
A relentless interview to sharpen a plan or design.
improve-codebase-architecture
mattpocock/skills
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
handoff
mattpocock/skills
Compact the current conversation into a handoff document for another agent to pick up.
domain-modeling
mattpocock/skills
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
codebase-design
mattpocock/skills
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.