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 nWave-ai/nWave --skill nw-ddd-eventsourcinggit clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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/nwave-ai/nwave/nw-ddd-eventsourcing)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-ddd-eventsourcing"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-ddd-eventsourcing/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/nwave-ai/nwave/nw-ddd-eventsourcing"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-ddd-eventsourcing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.01734 |
| Opus 5 | $0.00019 | $0.00867 |
| Sonnet 5 | $0.00008 | $0.00347 |
| Haiku 4.5 | $0.00004 | $0.00173 |
Grade A, and why
nw-ddd-eventsourcing 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event Sourcing and CQRS
Implementation patterns for DDD. Event Sourcing stores every state change as an immutable event and derives current state from replay. CQRS separates write and read models. These are tools, not mandatory architecture -- apply selectively to domains where they add value.
When to Use Event Sourcing
ES adds value when:
- Complete audit trail required (financial, regulatory, medical)
- Temporal queries needed ("what was the state on January 15?")
- Multiple views of same data (different read models for different consumers)
- Complex domain with rich business rules (natural fit with DDD aggregates)
- Event-driven integration with other systems
- Debugging requires replay ("what exactly happened?")
ES is overkill when:
- Simple CRUD with no audit requirements
- Team unfamiliar and project has no learning budget
- No business value from history
- Domain has no behavior (data in, data out)
Key question: "Does knowing the history of how we got here provide business value?" Yes -> consider ES. No -> traditional CRUD is simpler.
Core Concepts
Events as Facts
Events are immutable records of things that happened. Past tense: OrderPlaced, PaymentReceived, ItemShipped.
Event structure: Include all data needed to understand what happened (self-contained) | Use domain language | One event per meaningful business fact | Events carry data only, no behavior
Granularity: Too coarse (OrderUpdated { order: {...} }) loses what changed. Too fine (OrderFieldChanged { field, old, new }) is generic audit log. Just right (OrderConfirmed { orderId, confirmedBy, confirmedAt }) has clear business meaning.
The Event Store
Single source of truth. Core operations:
append(streamId, expectedVersion, events)-> success or concurrency conflictread(streamId)-> ordered list of eventssubscribe(filter)-> push notification for new events
Properties: Append-only (never modify/delete) | Ordered within stream | Immutable | Versioned (each event has position)
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 · 152 lines · 38 tokens per session scan A def99ce43e04
nw-ddd-eventsourcing is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 5d ago), licensed MIT. It adds 38 tokens to every session and 1,734 once invoked, about $0.0002 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 2026-09-03.
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