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Cqrs Implementation

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wshobson
cqrs-implementation

Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.

Overview

Publisherwshobson
Repositoryagents
Skill namecqrs-implementation
Stars
39.8K
Forks
4.2K
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by wshobson on GitHub. Read the source before you install it.

Installation

Install the Cqrs Implementation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/wshobson/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/plugins/backend-development/skills/cqrs-implementation .claude/skills/cqrs-implementation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cqrs Implementation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cqrs Implementation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cqrs Implementation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CQRS Implementation

Comprehensive guide to implementing CQRS (Command Query Responsibility Segregation) patterns.

When to Use This Skill

  • Separating read and write concerns
  • Scaling reads independently from writes
  • Building event-sourced systems
  • Optimizing complex query scenarios
  • Different read/write data models needed
  • High-performance reporting requirements

Core Concepts

1. CQRS Architecture

                    ┌─────────────┐
                    │   Client    │
                    └──────┬──────┘
              ┌────────────┴────────────┐
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │  Commands   │          │   Queries   │
       │    API      │          │    API      │
       └──────┬──────┘          └──────┬──────┘
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │  Command    │          │   Query     │
       │  Handlers   │          │  Handlers   │
       └──────┬──────┘          └──────┬──────┘
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │   Write     │─────────►│    Read     │
       │   Model     │  Events  │   Model     │
       └─────────────┘          └─────────────┘

2. Key Components

ComponentResponsibility
CommandIntent to change state
Command HandlerValidates and executes commands
EventRecord of state change
QueryRequest for data
Query HandlerRetrieves data from read model
ProjectorUpdates read model from events

Templates and detailed worked examples

Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.

Best Practices

Do's

  • Separate command and query models - Different needs
  • Use eventual consistency - Accept propagation delay
  • Validate in command handlers - Before state change
  • Denormalize read models - Optimize for queries
  • Version your events - For schema evolution

Don'ts

  • Don't query in commands - Use only for writes
  • Don't couple read/write schemas - Independent evolution
  • Don't over-engineer - Start simple
  • Don't ignore consistency SLAs - Define acceptable lag

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cqrs Implementation AI skill do?

Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.

Why use Cqrs Implementation on TypingMind?

Because you install it once and use it with any model. Cqrs Implementation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cqrs Implementation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wshobson/agents/tree/main/plugins/backend-development/skills/cqrs-implementation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cqrs Implementation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cqrs Implementation?

As many as you like. As long as a model supports skills, you can use Cqrs Implementation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cqrs Implementation AI skill free?

Yes. It is published on GitHub by wshobson under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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