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 TheBeardedBearSAS/claude-craft --skill cqrsgit clone --depth 1 https://github.com/TheBeardedBearSAS/claude-craftWrote 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/thebeardedbearsas/claude-craft/cqrs)<a href="https://agentmods.dev/skills/thebeardedbearsas/claude-craft/cqrs"><img src="https://agentmods.dev/badge/skills/thebeardedbearsas/claude-craft/cqrs/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/thebeardedbearsas/claude-craft/cqrs"><img src="https://agentmods.dev/badge/skills/thebeardedbearsas/claude-craft/cqrs.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 | $0.00037 | $0.00793 |
| Opus 5 | $0.00018 | $0.00396 |
| Sonnet 5 | $0.00007 | $0.00159 |
| Haiku 4.5 | $0.00004 | $0.00079 |
Grade A, and why
cqrs 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.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CQRS — Quick Reference
CQRS (Command Query Responsibility Segregation) sépare les opérations d'écriture et de lecture dans des modèles distincts. N'est pas par défaut — c'est une optimisation à activer quand le coût de la complexité est justifié.
Quand utiliser
| Pertinent | Pas pertinent |
|---|---|
| Domaine métier complexe avec règles d'invariants riches | CRUD simple, domaine pauvre |
| Ratio lectures/écritures > 10× | Petits projets, équipe junior |
| Audit / compliance (Event Sourcing naturel) | Cohérence immédiate requise |
| Read models hétérogènes (mobile vs analytics vs back-office) | Modèle de données stable et unique |
| Scale différencié reads vs writes (replicas, cache, search) | Charge faible, monolithe modeste |
Règle d'or : commencer par une architecture classique. Migrer vers CQRS lorsqu'au moins 2 des cas pertinents sont présents simultanément.
Architecture en 30 secondes
[ User ]
↓
[ Command ]──────────▶ [ Write Model (Domain) ]
↓ persist + emit
[ Event(s) ]
↓
[ Query ] ◀───── [ Read Model (denormalised) ] ◀── projections
- Command side : modèle normalisé, focus invariants métier. Écrit, ne lit que ce qui est nécessaire à la validation.
- Query side : modèle dénormalisé, focus performance lecture. N'a pas de logique métier.
- Projections : transforment les events en read models. Eventually consistent.
Trade-off central
| Bénéfice | Coût |
|---|---|
| Scale indépendant lecture / écriture | Eventual consistency (≈ 50-500 ms latency typique) |
| Read models taillés pour chaque besoin | Plus de code à maintenir (2 modèles) |
| Event Sourcing devient facile à brancher | Debugging plus complexe (event flow) |
| Audit trail naturel | Migration tardive très coûteuse |
Patterns associés (souvent ensemble)
- Event Sourcing : stocker la séquence d'events comme source de vérité, le write model est reconstruit en replay.
- Saga / Process Manager : orchestrer des transactions distribuées via events.
- Outbox Pattern : garantir l'atomicité publication event + write DB.
- Materialized Views : projections persistées en table dédiée pour query speed.
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.
- 6d ago First seen · 67 lines · 0 tokens per session scan A 9cc74ae9486b
cqrs is a skill published in the GitHub repository TheBeardedBearSAS/claude-craft (105 stars, last pushed 7d ago), licensed MIT. It adds 37 tokens to every session and 793 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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