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 hamzaPixl/pixl-ai --skill ddd-patterngit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote 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/hamzapixl/pixl-ai/ddd-pattern)<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/ddd-pattern"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/ddd-pattern.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.00970 |
| Opus 5 | $0.00029 | $0.00485 |
| Sonnet 5 | $0.00012 | $0.00194 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
ddd-pattern 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 7d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
This skill applies Domain-Driven Design (DDD) tactical and strategic patterns to an existing codebase. It starts with domain discovery — analyzing existing code to identify implicit domain concepts, relationships, and bounded context boundaries. It then models the domain explicitly, separates the domain layer from infrastructure, optionally adds domain events, and verifies the result.
The skill adapts to the target project's language (Python or TypeScript), framework, and existing architecture.
Why DDD matters: Bounded contexts prevent coupling by giving each concept one authoritative home — when "User" means different things in Auth vs Billing, separate models prevent changes in one from breaking the other. Private constructors on entities enforce domain invariants at the creation boundary, making invalid states unrepresentable.
Required References
Before starting, read references/backend/ddd-patterns.md for tactical patterns (entities, value objects, aggregates, repositories, domain events).
Step 1: Discovery
Analyze existing code to identify domain concepts, map relationships between entities, detect implicit bounded contexts, and catalog business rules buried in service or controller code.
If the user provides a domain analysis or explicit model, parse it into discovery format and skip to Step 2.
Actions:
- Scan the codebase for entity-like classes, service classes, and data models
- Identify implicit domain concepts from naming, relationships, and business logic
- Map relationships between entities (associations, dependencies, event flows)
- Detect bounded context boundaries (where concepts change meaning)
- Catalog business rules currently embedded in controllers/services
Step 2: Model
Define bounded contexts with clear boundaries, model entities with identity and lifecycle, extract value objects for descriptive concepts, define aggregates with invariants and consistency boundaries.
Key patterns (see reference.md for details):
What ships with it
1 file 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.
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.
- 7d ago First seen · 85 lines · 58 tokens per session scan A d39f1d45c5ed
ddd-pattern is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 58 tokens to every session and 970 once invoked, about $0.0003 per session on Opus 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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