CQRS Implementation
Separates read and write models with CQRS patterns for scalable, event-sourced systems.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/cqrs-implementation-wshobson/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
Teaches Claude how to apply Command Query Responsibility Segregation: splitting an app into command and query sides, wiring command handlers, events, projectors, and query handlers, and keeping read and write models independent. Covers when CQRS is worth it (scaling reads separately, event sourcing, complex reporting) and the consistency tradeoffs it introduces. Reach for it when designing or refactoring a service that needs different read and write data models or independent read scaling.
What this skill does
What it does: Gives Claude a reference for implementing CQRS, including the command/query flow architecture and the components that connect the two sides.
- Maps the full CQRS topology: separate command and query APIs feeding command and query handlers, with the write model emitting events that update the read model.
- Defines each component's responsibility: command (intent to change state), command handler (validate and execute), event (record of change), query, query handler, and projector (rebuilds the read model from events).
- Lists concrete signals for when CQRS fits: independent read scaling, event-sourced systems, divergent read/write models, and high-performance reporting.
- Encodes best practices and anti-patterns: denormalize read models, validate before state changes, version events for schema evolution, accept eventual consistency, and avoid querying inside commands or coupling read/write schemas.
- Points to a
references/details.mdtemplate library for concrete, worked CQRS implementation examples.
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