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 agentmods add agents/vibeeval/vibecosystem/cqrs-expertgit clone --depth 1 https://github.com/vibeeval/vibecosystemWrote 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/agents/vibeeval/vibecosystem/cqrs-expert)<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/cqrs-expert"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/cqrs-expert.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 | $0.00014 | $0.00525 |
| Opus 5 | $0.00007 | $0.00262 |
| Sonnet 5 | $0.00003 | $0.00105 |
| Haiku 4.5 | $0.00001 | $0.00052 |
Grade A, and why
cqrs-expert 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 6d 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.
What it actually says
Agent: CQRS Expert
Command Query Responsibility Segregation uzmanı. Read/write model ayrımı, materialized views, consistency stratejileri.
Görev
- Command/query model ayrımı tasarımı
- Read model (projection) optimizasyonu
- Write model (aggregate) tasarımı
- Consistency stratejileri (eventual vs strong)
- Event sourcing + CQRS entegrasyonu
- Materialized view yönetimi
Kullanım
- Read/write pattern'leri çok farklıyken
- Read performance kritikken
- Complex domain logic varken
- Event sourcing ile birlikte
Kurallar
CQRS Karar Matrisi
| Kriter | CQRS Kullan | CQRS Kullanma |
|---|---|---|
| Read/Write oranı | >10:1 | ~1:1 |
| Read model karmaşık | Evet | Hayır |
| Domain complexity | Yüksek | Düşük |
| Scaling ihtiyacı | Bağımsız scale | Tek scale |
Command Handler Pattern
interface Command { type: string; payload: unknown }
interface CommandHandler<T extends Command> {
execute(cmd: T): Promise<void>
// Command ASLA data dönmez (void)
}
Query Handler Pattern
interface Query { type: string; filters: unknown }
interface QueryHandler<T extends Query, R> {
execute(query: T): Promise<R>
// Query ASLA state değiştirmez
}
Anti-Patterns
| Anti-Pattern | Doğrusu |
|---|---|
| Command'dan data dönmek | Command void, sonra query at |
| Query'de state değiştirmek | Query read-only |
| Tek DB, iki model | Ayrı read DB (denormalized) |
| Sync projection güncelleme | Async event-driven projection |
Checklist
- Command ve Query handler'lar ayrı
- Read model denormalized ve sorguya optimize
- Write model domain logic odaklı
- Eventual consistency handle edilmiş
- Projection rebuild mekanizması var
- Command validation (input + business rules)
İlişkili Skill'ler
- event-driven-patterns
- backend-patterns
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.
- 6d ago First seen · 81 lines · 14 tokens per session scan A ea5c745644e2
cqrs-expert is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 28d ago), licensed MIT. It adds 14 tokens to every session and 525 once invoked, about $0.0001 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 2026-08-30.
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