sickn33/agentic-awesome-skills

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.

First seen Jan 28, 2026

Installation

$ npx skills add sickn33/agentic-awesome-skills --skill cqrs-implementation

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
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GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 46.2K
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,591 B
  • docs SUMMARY.md 210 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 235 installs

SKILL.md

CQRS Implementation

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

Use this skill when

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

Do not use this skill when

  • The domain is simple and CRUD is sufficient
  • You cannot operate separate read/write models
  • Strong immediate consistency is required everywhere

Instructions

  • Identify read/write workloads and consistency needs.
  • Define command and query models with clear boundaries.
  • Implement read model projections and synchronization.
  • Validate performance, recovery, and failure modes.
  • If detailed patterns are required, open resources/implementation-playbook.md.

Resources

  • resources/implementation-playbook.md for detailed CQRS patterns and templates.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.