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.
Install with Tessl CLI
npx tessl i github:wshobson/agents --skill cqrs-implementationOverall
score
73%
Does it follow best practices?
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npx tessl skill review --optimize ./path/to/skillEvaluation — 88%
↑ 1.54xAgent success when using this skill
Validation for skill structure
Discovery
75%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a competent description that clearly identifies the CQRS pattern and provides explicit 'Use when' guidance, making it easy for Claude to know when to select it. However, it could be stronger by listing more concrete implementation actions and including additional natural trigger terms that users might use when asking about this pattern.
Suggestions
Add more specific concrete actions such as 'create command handlers, build read projections, implement event stores, design aggregate boundaries'
Expand trigger terms to include variations like 'command handler', 'query handler', 'read model', 'write model', 'event store', 'separate reads from writes'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (CQRS) and mentions some actions like 'separating read and write models' and 'optimizing query performance', but doesn't list multiple concrete implementation actions (e.g., creating command handlers, building read projections, implementing event stores). | 2 / 3 |
Completeness | Clearly answers both what ('Implement Command Query Responsibility Segregation for scalable architectures') and when ('Use when separating read and write models, optimizing query performance, or building event-sourced systems') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Includes relevant technical terms like 'CQRS', 'read and write models', 'event-sourced systems', but misses common variations users might say such as 'command handler', 'query handler', 'read model', 'write model', 'event store', or the full acronym expansion. | 2 / 3 |
Distinctiveness Conflict Risk | CQRS is a specific architectural pattern with distinct terminology; unlikely to conflict with general coding skills or other architecture patterns. The triggers are specific enough to avoid false matches. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
65%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides excellent actionable code templates for CQRS implementation with complete, executable Python examples covering commands, queries, handlers, and FastAPI integration. However, it lacks a clear implementation workflow with validation steps, and the content is verbose for a skill file - it reads more like comprehensive documentation than a focused skill guide. The 'When to Use' section and some explanatory content could be trimmed.
Suggestions
Add a clear numbered workflow section at the top showing the sequence for implementing CQRS (e.g., '1. Define commands → 2. Create handlers → 3. Set up event store → 4. Build projections → 5. Verify sync') with validation checkpoints
Move detailed templates (especially Templates 4 and 5) to separate reference files like PROJECTIONS.md and CONSISTENCY.md, keeping SKILL.md as a concise overview
Remove the 'When to Use This Skill' section - Claude can determine applicability from context
Add explicit validation/verification steps for the read model synchronization process, such as how to verify projections are correctly catching up
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill includes some unnecessary sections like 'When to Use This Skill' that Claude can infer, and the architecture diagram while helpful adds tokens. The templates are comprehensive but could be more focused - some boilerplate code could be trimmed. | 2 / 3 |
Actionability | Provides fully executable Python code with complete implementations for commands, queries, handlers, FastAPI integration, and read model synchronization. Code is copy-paste ready with proper imports and type hints. | 3 / 3 |
Workflow Clarity | While the templates show the components clearly, there's no explicit step-by-step workflow for implementing CQRS in a project. Missing validation checkpoints for the synchronization process and no clear sequence for setting up the architecture from scratch. | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with templates and best practices sections, but it's a monolithic document with 400+ lines. The advanced topics like eventual consistency handling and read model synchronization could be split into separate reference files. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
75%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 12 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (555 lines); consider splitting into references/ and linking | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
license_field | 'license' field is missing | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 12 / 16 Passed | |
- Reviewed
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