architecture-patterns

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.

Quality

—

Does it follow best practices?

Impact

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No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is actionable and well-structured with real code and a clean reference hierarchy. The main drag is conciseness — the Core Concepts section explains standard architecture definitions Claude already knows — and the absence of explicit validation checkpoints in a formal workflow.

Suggestions

Trim the 'Core Concepts' section to the non-obvious rules (dependency direction, port/adapter split) and drop textbook definitions of Entities/Value Objects/Aggregates that Claude already knows.

Collapse the opening paragraph that restates the frontmatter description to avoid redundant tokens at the top of the body.

If a recommended design/refactor procedure exists, present it as a numbered workflow with explicit validation checkpoints (e.g., verify no inward dependency violations before proceeding) to lift workflow_clarity.

Dimension	Reasoning	Score
Conciseness	Mostly lean with terse lists and a concrete code example, but the 'Core Concepts' section restates textbook DDD/Clean Architecture definitions (Entities, Value Objects, Aggregates) that Claude already knows, and the opening line repeats the frontmatter description.	2 / 3
Actionability	Provides a fully executable Python in-memory adapter test example plus concrete troubleshooting remedies with specific file-path rules (e.g., 'use_cases/ imports only from domain/'), giving copy-paste-ready guidance.	3 / 3
Workflow Clarity	Troubleshooting entries give clear symptom-to-fix sequences, but there is no explicit multi-step workflow with validation checkpoints; for a design skill the sequencing is reasonable but checkpoints are implicit.	2 / 3
Progressive Disclosure	Clear overview in the body with two well-signaled, one-level-deep references (references/details.md and references/advanced-patterns.md), both of which exist and do not nest further, splitting content appropriately.	3 / 3
	Total	10 / 12 Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it states concrete capabilities, provides explicit and varied use-when triggers, uses third person, and is clearly distinguishable from other skills. No significant weaknesses to address.

Dimension	Reasoning	Score
Specificity	Names three concrete patterns (Clean Architecture, Hexagonal, DDD) and multiple specific actions: designing architecture for a microservice, refactoring a monolith to bounded contexts, implementing hexagonal/onion patterns, and debugging dependency cycles.	3 / 3
Completeness	Explicitly states what it does ('Implement proven backend architecture patterns including...') and when to use it via a clear 'Use this skill when...' clause with multiple explicit triggers.	3 / 3
Trigger Term Quality	Uses natural terms engineers actually say — 'clean architecture', 'new microservice', 'refactoring a monolith', 'bounded contexts', 'hexagonal/onion architecture', 'dependency cycles' — with good coverage of common phrasings.	3 / 3
Distinctiveness Conflict Risk	Occupies a clear niche (backend architecture patterns) with distinct triggers tied to architecture-specific scenarios, making it unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: wshobson/agents
Commit: 5cc2549

Reviewed: 6 days ago

Table of Contents

Discovery Implementation Validation

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