tactical-ddd▌
tech-leads-club/agent-skills · updated May 23, 2026
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Detects anemic domain models, validates and refactors them into rich domain models, and enforces tactical DDD patterns (Entities, Value Objects, Aggregates, Domain Services, Domain Events). Use when the user asks to validate, review, or check domain models or DDD code; detect anemia; refactor domain objects; improve encapsulation; or mentions terms like "anemic model", "rich domain", "aggregate", "value object", "domain event", "ubiquitous language", "is this good DDD", "does this follow DDD", or "check my domain". Do NOT use for module or service boundary design, architectural decomposition, strategic DDD context mapping, or code outside the domain layer (DTOs, controllers, infrastructure adapters).
| name | tactical-ddd |
| description | Detects anemic domain models, validates and refactors them into rich domain models, and enforces tactical DDD patterns (Entities, Value Objects, Aggregates, Domain Services, Domain Events). Use when the user asks to validate, review, or check domain models or DDD code; detect anemia; refactor domain objects; improve encapsulation; or mentions terms like "anemic model", "rich domain", "aggregate", "value object", "domain event", "ubiquitous language", "is this good DDD", "does this follow DDD", or "check my domain". Do NOT use for module or service boundary design, architectural decomposition, strategic DDD context mapping, or code outside the domain layer (DTOs, controllers, infrastructure adapters). |
Tactical DDD — Rich Domain Modeling
Workflow
Determine the user's intent first:
| Intent | Phases to run |
|---|---|
| "validate / review / check / is this correct?" | Phase 1 + 2 only → report findings, ask before refactoring |
| "fix / refactor / improve / clean up" | Phase 1 + 2 + 3 |
| "how should I design / model this?" | Load reference.md directly |
Phase 1 — Detect
Load detection.md and scan the target code for anemia signals. Produce a severity score and list of affected classes.
Phase 2 — Assess
For each affected class, determine the correct building block:
| Has unique identity tracked over time? | Has invariants tying multiple objects? | → Building Block |
|---|---|---|
| Yes | — | Entity |
| No | — | Value Object |
| Yes (root) + children with shared invariants | Yes | Aggregate |
| Operation spans multiple Aggregates/doesn't belong to any | — | Domain Service |
Prefer Value Objects over Entities. Prefer small Aggregates over large ones.
If intent was validate/review: stop here. Report findings using the output format below. Ask "Would you like me to apply these fixes?" before proceeding.
Phase 3 — Refactor
Load refactoring.md for step-by-step moves. Apply in this order:
- Replace setter chains with a single expressive method
- Move service logic into the Aggregate that owns it
- Add business guards at the top of each method
- Publish a Domain Event after each successful state change
- Replace primitive types with Value Objects
For deep pattern questions (boundary design, event modeling, service vs. entity decision), load reference.md.
Quick Anemia Signals (scan first)
public setX() / public setY() → behaviour should be encapsulated
service.doX(entity, ...) → logic likely belongs in entity
entity.setA(); entity.setB(); ... → setter chain = missing intent method
no domain methods beyond getters → pure data bag
Golden Rules
- Behaviour with data — Objects own both state and the operations that change it
- Ubiquitous Language — Method names come from the domain, not CRUD (
commitTo, notsetStatus) - Small Aggregates — Root + Value Objects by default; add child Entities only for true invariants
- One transaction = one Aggregate — Cross-Aggregate rules use eventual consistency via Domain Events
- Reference by ID — Never hold object references to other Aggregates
- Value Objects first — Use Entities only when individual identity is essential
- Domain Services sparingly — Excessive services → anemic model
- Protect invariants — The Aggregate is the last line of defence; never trust the caller
Output Format
When reviewing code, report:
## Anemia Diagnosis: <ClassName>
Severity: [None | Mild | Moderate | Severe]
Issues:
- <description of problem>
Recommended refactoring:
- <specific move from refactoring.md>
When refactoring, show a before/after diff for each class touched.
How to use tactical-ddd on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add tactical-ddd
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches tactical-ddd from GitHub repository tech-leads-club/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate tactical-ddd. Access the skill through slash commands (e.g., /tactical-ddd) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★43 reviews- ★★★★★Ava Perez· Dec 12, 2024
tactical-ddd fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Anika Johnson· Dec 8, 2024
tactical-ddd is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Anika Mensah· Nov 27, 2024
Solid pick for teams standardizing on skills: tactical-ddd is focused, and the summary matches what you get after install.
- ★★★★★Zara Jain· Nov 3, 2024
We added tactical-ddd from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kabir Yang· Oct 22, 2024
Solid pick for teams standardizing on skills: tactical-ddd is focused, and the summary matches what you get after install.
- ★★★★★Luis Smith· Oct 18, 2024
We added tactical-ddd from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Valentina Okafor· Sep 25, 2024
tactical-ddd reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kiara Malhotra· Sep 21, 2024
Registry listing for tactical-ddd matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yash Thakker· Sep 17, 2024
Keeps context tight: tactical-ddd is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Rahul Santra· Sep 13, 2024
Useful defaults in tactical-ddd — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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