python-patterns

Pythonic イディオム、PEP 8標準、型ヒント、堅牢で効率的かつ保守可能なPythonアプリケーションを構築するためのベストプラクティス。

1.13x

Quality

37%

Does it follow best practices?

Impact

90%

1.13x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./docs/ja-JP/skills/python-patterns/SKILL.md

Quality

Discovery

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 identifies its domain (Python best practices and standards) but lacks concrete actions and explicit trigger guidance. It reads more like a topic label than an actionable skill description. The absence of a 'Use when...' clause and specific verbs significantly weakens its utility for skill selection among multiple candidates.

Suggestions

Add an explicit 'Use when...' clause with trigger scenarios, e.g., 'Use when the user asks for Python code review, PEP 8 compliance, adding type hints, or refactoring Python code for readability and maintainability.'

Replace the abstract noun phrase structure with concrete action verbs, e.g., 'Reviews Python code for PEP 8 compliance, adds type annotations, refactors code to use Pythonic idioms, and suggests performance improvements.'

Include natural trigger terms users would say, such as 'code review', 'refactor', 'clean code', 'Python style', 'linting', '.py files', to improve keyword coverage.

Dimension	Reasoning	Score
Specificity	Names the domain (Python) and mentions some specific areas like 'Pythonic idioms', 'PEP 8 standards', 'type hints', and 'best practices', but these are more like categories than concrete actions. No specific verbs describing what the skill does (e.g., 'refactors code', 'adds type annotations', 'lints for PEP 8 compliance').	2 / 3
Completeness	The description addresses 'what' at a high level (Python best practices, PEP 8, type hints) but completely lacks any 'when' clause or explicit trigger guidance. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and since the 'what' is also somewhat vague, this scores a 1.	1 / 3
Trigger Term Quality	Includes relevant keywords like 'PEP 8', 'type hints' (型ヒント), 'Pythonic', and 'Python' that users might mention. However, it misses common variations and natural phrases users would say such as 'code review', 'refactor', 'clean code', 'style guide', 'linting', or file extensions like '.py'.	2 / 3
Distinctiveness Conflict Risk	While it focuses on Python coding standards and idioms specifically, it could easily overlap with general Python development skills, code review skills, or any Python-related skill. The scope of 'building robust, efficient, and maintainable Python applications' is broad enough to conflict with many Python-related skills.	2 / 3
	Total	7 / 12 Passed

Implementation

42%

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

This skill is essentially a comprehensive Python tutorial/reference that teaches Claude things it already knows deeply—type hints, list comprehensions, context managers, decorators, async/await, dataclasses, etc. While the code examples are high quality and executable, the skill wastes enormous context window space on fundamental Python knowledge. It would be far more effective as a brief set of project-specific conventions or constraints rather than a general Python education document.

Suggestions

Reduce content by 80%+ by removing patterns Claude already knows (decorators, comprehensions, context managers, type hints basics) and focus only on project-specific conventions or non-obvious preferences.

Split into a brief SKILL.md overview (under 50 lines) with references to separate files like PATTERNS.md, TOOLING.md, and ANTIPATTERNS.md for progressive disclosure.

Focus on what's unique or opinionated: e.g., 'Always use ruff over pylint', 'Prefer dataclasses over NamedTuple', 'Use src/ layout' — decisions Claude can't infer on its own.

Add a concise decision table or flowchart for when to use which pattern (e.g., threads vs multiprocessing vs async) rather than explaining each from scratch.

Dimension	Reasoning	Score
Conciseness	This is extremely verbose at ~500+ lines, covering fundamental Python concepts (list comprehensions, context managers, decorators, type hints, etc.) that Claude already knows thoroughly. Nearly every section explains basic Python knowledge that adds no new information for Claude. The 'readability matters' section literally teaches good vs bad variable naming.	1 / 3
Actionability	The code examples are fully executable, concrete, and copy-paste ready throughout. Every pattern includes working Python code with clear good/bad comparisons, and the tooling section provides specific CLI commands and complete pyproject.toml configuration.	3 / 3
Workflow Clarity	The skill is a reference/pattern catalog rather than a multi-step workflow, so sequencing is less critical. However, the 'when to activate' section provides clear triggers, and the tooling section lists commands in a logical order. No validation checkpoints or feedback loops are present for operations like package setup or refactoring.	2 / 3
Progressive Disclosure	This is a monolithic wall of text with no references to external files and no layered structure. All content—from basic idioms to advanced concurrency patterns to tooling configuration—is dumped into a single massive file with no progressive disclosure or navigation aids.	1 / 3
	Total	7 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (750 lines); consider splitting into references/ and linking	Warning

	Total	10 / 11 Passed

Repository: affaan-m/everything-claude-code
Commit: 928076c

Reviewed: 3 days ago

Table of Contents

Discovery Implementation Validation

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