Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add svngoku/coding-agents-skills --skill dddgit clone --depth 1 https://github.com/svngoku/coding-agents-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/svngoku/coding-agents-skills/ddd)<a href="https://agentmods.dev/skills/svngoku/coding-agents-skills/ddd"><img src="https://agentmods.dev/badge/skills/svngoku/coding-agents-skills/ddd/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/svngoku/coding-agents-skills/ddd"><img src="https://agentmods.dev/badge/skills/svngoku/coding-agents-skills/ddd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00137 | $0.01335 |
| Opus 5.5 | $0.00055 | $0.00534 |
| Sonnet 5.5 | $0.00027 | $0.00267 |
| Haiku 4.5 | $0.00014 | $0.00134 |
Grade A, and why
ddd scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain-Driven Design Skill
Apply DDD to build software that reflects deep understanding of the business domain.
Quick Reference
| Task | Reference |
|---|---|
| Bounded contexts, subdomains, context maps | strategic-design.md |
| Entities, value objects, aggregates, repositories | tactical-design.md |
| Hexagonal, CQRS, Event Sourcing, Clean Architecture | architecture-patterns.md |
| Event Storming facilitation & documentation | event-storming.md |
| Python implementations (Pydantic, SQLAlchemy, FastAPI) | python-patterns.md |
| TypeScript implementations (NestJS, TypeORM, Prisma) | typescript-patterns.md |
| DDD code review criteria | code-review.md |
Core Workflow
1. Identify the Task Type
Designing new system? → Start with strategic design, then tactical Refactoring existing code? → Assess current state, identify bounded contexts, refactor incrementally Generating scaffolding? → Determine patterns needed, generate code Event Storming? → Follow facilitation guide Code review? → Apply DDD checklist
2. Strategic Before Tactical
Always establish strategic design first:
- Identify subdomains (Core, Supporting, Generic)
- Define bounded contexts and their boundaries
- Map context relationships (upstream/downstream, conformist, ACL, etc.)
- Establish ubiquitous language per context
3. Select Architecture Pattern
Choose based on domain complexity and requirements:
| Pattern | When to Use |
|---|---|
| Layered | Simple CRUD, low complexity |
| Hexagonal | Need to isolate domain from infrastructure |
| Clean Architecture | Complex business rules, multiple delivery mechanisms |
| CQRS | Different read/write models, complex queries |
| Event Sourcing | Audit trail required, temporal queries, event-driven |
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- eval.yaml 1.2 KB
- graders/check.py 14 KB runs code
- instructions/checkout-domain-model.md 3.4 KB
- references/architecture-patterns.md 21 KB
- references/code-review.md 9.6 KB
- references/event-storming.md 13 KB
- references/python-patterns.md 20 KB
- references/strategic-design.md 7.9 KB
- references/tactical-design.md 11 KB
- references/typescript-patterns.md 23 KB
- rubrics/quality.md 3.0 KB
- solutions/reference-checkout-domain 7.1 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago Changed 140d2efd7a5e
- 1mo ago First seen · 130 lines · 137 tokens per session scan A 90b9411e7e62
ddd is a skill published in the GitHub repository svngoku/coding-agents-skills (12 stars, last pushed 3d ago), licensed MIT. It adds 137 tokens to every session and 1,335 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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