Atlas / Skills / nwave-ai / Nw Ddd Strategic

Nw Ddd StrategicSAFE

skills/nwave-ai/nw-ddd-strategic

AI agents that guide you from idea to working code, with you in control at every step.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
617
01

Overview

AI agents that guide you from idea to working code, with you in control at every step.

Read from source at commit 1a864ec81cdeOBSERVED · 2026-10-14
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02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: nw-ddd-strategic
description: Strategic DDD — bounded context discovery, context mapping patterns, subdomain classification, ubiquitous language, and organizational alignment
user-invocable: false
disable-model-invocation: true
---

# Strategic DDD

Domain discovery and boundary definition at the organizational level. Strategic DDD answers: "Where are the boundaries?" and "How do contexts relate?"

## Subdomain Classification

Subdomains exist in the problem space. Classify before modeling.

| Type | Competitive advantage | Build or buy | DDD investment | Staffing |
|------|----------------------|--------------|----------------|----------|
| Core | Yes, unique differentiator | Build in-house | Full strategic + tactical | Senior talent |
| Supporting | No, enables core | Build (simplified) or outsource | Pragmatic tactical | Mid-level |
| Generic | No, commodity | Buy/integrate (Stripe, Auth0) | Minimal/none | Junior/integration |

**Decision heuristic**: If two competitors solve this the same way, it's Generic. If your approach gives you an edge, it's Core. Everything else is Supporting.

## Bounded Context Discovery

A bounded context is a software boundary within which a model is consistent. Different from subdomains (problem-space). They should align but are independent concepts.

### Discovery Techniques

**Language divergence** (primary signal): When the same word means different things to different groups, you've found a boundary. "Account" in billing vs. "Account" in identity. "Product" in catalog vs. "Product" in inventory.

**Organizational structure**: Teams that communicate frequently often share a context. Teams with formal handoffs often have separate contexts. Conway's Law applies.

**Consistency requirements**: Where true invariants must be maintained transactionally defines aggregate boundaries, which cluster into contexts.

**EventStorming Big Picture**: Domain events placed on timeline. When events cluster into distinct swimlanes with different actors and vocabulary, those are context candidates.

**Domain Storytelling**: Actors perform activities on work objects. When actors, activities, or work objects change meaning, you've crossed a boundary.

### Boundary Validation Checklist

- [ ] Each context has its own ubiquitous language (no term means two things)
- [ ] One team owns one context (no shared ownership)
- [ ] Context is independently deployable (no mandatory co-deployment)
- [ ] Internal model changes don't ripple to other contexts
- [ ] Data that crosses boundaries is explicitly mapped (no implicit sharing)

### Common Mistakes

1. **Context = microservice**: A context may contain multiple services; a service may handle a subdomain within a larger context
2. **Too large**: Conflicting models coexist, vocabulary is ambiguous -- split
3. **Too small**: Excessive cross-context communication, simple operations need sagas -- merge
4. **Database-first**: Sharing a database between contexts couples their models implicitly

## Context Mapping Patterns

Nine patterns describing how bounded contexts relate. Draw the context map before writing code.

### Mutually Dependent

**Partnership**: Two contexts evolve together. Both teams coordinate releases. Use when: genuinely reciprocal dependency, tight collaboration feasible. Risk: high coordination cost.

**Shared Kernel**: Small shared model subset both contexts depend on. Must be small, explicitly versioned, jointly owned. Changes require agreement from both teams.

### Upstream/Downstream

**Customer-Supplier**: Upstream serves downstream's needs. Downstream negotiates what upstream provides. Structured relationship with explicit API contracts.

**Conformist**: Downstream adopts upstream's model as-is. No negotiation. Use when: integration simplicity outweighs design freedom, or upstream won't accommodate.

**Anti-Corruption Layer (ACL)**: Downstream creates a translation layer to isolate its model from upstream's. Essential for: legacy integration, poor upstream models, protecting domain purity.

**Open Host Service (OHS)**: Upstream provides a well-defined API for multiple downstream consumers. Standardized protocol (REST, gRPC, GraphQL).

**Published Language**: Shared schema or format for inter-context communication. Examples: iCalendar, vCard, JSON Schema, Protocol Buffers.

### Independent

**Separate Ways**: No integration. Contexts have no meaningful dependency. Duplication is acceptable when coupling cost exceeds duplication cost.

**Big Ball of Mud**: Recognition pattern only. Demarcate and quarantine legacy systems. Draw a boundary around them, communicate through ACL.

### Selection Heuristic

```
Do the teams need to coordinate releases?
  YES -> Do both depend on each other equally?
    YES -> Partnership (if feasible) or Shared Kernel (if small overlap)
    NO  -> Customer-Supplier (negotiate API)
  NO  -> Is upstream model acceptable?
    YES -> Conformist (adopt as-is)
    NO  -> Anti-Corruption Layer (translate)
  Independent? -> Separate Ways
  Legacy mess? -> Big Ball of Mud + ACL
```

## Ubiquitous Language

A rigorous vocabulary shared between developers and domain experts, scoped per bounded context.

### Rules

1. Domain terms in code: class names, method names, variable names reflect domain language
2. Same term, different context: "Order" in Sales vs. "Order" in Fulfillment are different concepts -- this is expected and healthy
3. When the model is hard to express in code, the language needs refinement
4. Resolve conflicts immediately: if developers and domain experts use different words for the same concept, pick one and enforce it

### Building the Language

- Maintain a glossary per bounded context (not per system)
- Review glossary during modeling sessions
- When new terms emerge, add them; when terms change, update code
- Code review should catch language violations ("this variable should be called X, not Y")

## Context Map Visualization

Use Mermaid flowchart for context maps:

03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-14 · audit v0.4.1 · source sha 1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-ddd-strategic.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-141a864ec81cdeSAFEB89first audit
05

Questions

What does the Nw Ddd Strategic skill do?

AI agents that guide you from idea to working code, with you in control at every step.

Is Nw Ddd Strategic safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Nw Ddd Strategic access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (1a864ec81cde), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

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