django-patterns

Django架构模式，使用DRF设计REST API，ORM最佳实践，缓存，信号，中间件，以及生产级Django应用程序。

Quality

37%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./docs/zh-CN/skills/django-patterns/SKILL.md

Quality

Content

42%

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

The skill provides comprehensive, executable Django code examples covering many important patterns, which is its primary strength. However, it is far too verbose for a skill file—most of this content represents standard Django/DRF patterns that Claude already knows well. The monolithic structure with no progressive disclosure and no workflow sequencing or validation checkpoints significantly reduces its effectiveness as a skill document.

Suggestions

Reduce content by 70-80%: focus only on project-specific conventions, non-obvious patterns, and decisions that deviate from Django defaults. Remove standard boilerplate like basic settings, common model fields, and well-known DRF patterns.

Split into multiple files: create a concise SKILL.md overview (~50 lines) with references to separate files like MODELS.md, DRF_PATTERNS.md, CACHING.md, and PERFORMANCE.md.

Add workflow sequences with validation checkpoints, e.g., 'After creating models: 1. Run makemigrations 2. Review migration file 3. Run migrate 4. Verify with shell query'.

Remove explanations of concepts Claude already knows (N+1 queries, select_related purpose, what signals are) and instead focus on project-specific rules like 'Always use service layer for multi-model operations' as concise directives.

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~500+ lines. Much of this is standard Django boilerplate that Claude already knows (settings configuration, basic model definitions, standard DRF patterns). The full settings files, basic CRUD ViewSets, and common patterns like select_related vs N+1 are well-known to Claude and don't need exhaustive reproduction. The closing platitude about maintainability adds no value.	1 / 3
Actionability	The code examples are concrete, executable, and copy-paste ready. Every pattern includes complete, runnable Python code with proper imports, class definitions, and usage examples. The serializer, ViewSet, service layer, and middleware examples are all fully functional.	3 / 3
Workflow Clarity	The skill presents patterns as isolated code blocks without a clear workflow for building a Django project step-by-step. There are no validation checkpoints (e.g., run migrations, test endpoints, verify cache behavior). For a production-grade skill involving database operations and deployment settings, the lack of verification steps is a notable gap.	2 / 3
Progressive Disclosure	This is a monolithic wall of text with no references to external files. All content—settings, models, serializers, views, caching, signals, middleware, performance—is inlined in a single massive document. This would benefit enormously from splitting into separate files (e.g., MODELS.md, DRF.md, CACHING.md, PERFORMANCE.md) with a concise overview in the main SKILL.md.	1 / 3
	Total	7 / 12 Passed

Description

32%

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 provides a reasonable topic-level overview of Django-related capabilities but reads as a comma-separated list of topics rather than a clear skill description with concrete actions. It critically lacks any 'Use when...' clause to guide Claude on when to select this skill, and the Chinese language mixed with English technical terms may affect matching depending on the user's language.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about Django project architecture, building REST APIs with Django REST Framework, optimizing Django ORM queries, or deploying Django applications to production.'

Convert the topic list into concrete action phrases, e.g., 'Designs REST APIs using Django REST Framework, optimizes ORM queries, implements caching strategies, configures middleware and signals for Django applications.'

Include additional natural trigger terms users might say, such as 'Django project', 'Django views', 'serializers', 'Django models', 'Django deployment', 'database optimization'.

Dimension	Reasoning	Score
Specificity	The description names the domain (Django) and lists several specific areas like DRF REST API design, ORM best practices, caching, signals, middleware, and production-grade Django apps. However, it reads more like a topic list than concrete actions — it doesn't use action verbs like 'design', 'implement', or 'configure' consistently.	2 / 3
Completeness	The description answers 'what' at a topic level but completely lacks any 'when should Claude use it' guidance. There is no 'Use when...' clause or equivalent explicit trigger guidance, which per the rubric should cap completeness at 2, and since the 'what' is also more of a topic list than clear capability description, this falls to 1.	1 / 3
Trigger Term Quality	Includes relevant technical keywords like 'Django', 'DRF', 'REST API', 'ORM', 'caching', 'signals', 'middleware' that users might mention. However, it misses common variations and natural language terms users might say (e.g., 'Django project', 'Django views', 'serializers', 'database queries', 'Django deployment').	2 / 3
Distinctiveness Conflict Risk	Django is a specific enough framework to provide some distinctiveness, but the broad scope covering architecture, APIs, ORM, caching, signals, and middleware could overlap with general Python skills, web development skills, or API design skills.	2 / 3
	Total	7 / 12 Passed

Validation

81%

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 — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (735 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	9 / 11 Passed

Repository: affaan-m/everything-claude-code
Commit: ec92b52

Reviewed: 3 days ago

Table of Contents

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