python-pro

Use when building Python 3.11+ applications requiring type safety, async programming, or robust error handling. Generates type-annotated Python code, configures mypy in strict mode, writes pytest test suites with fixtures and mocking, and validates code with black and ruff. Invoke for type hints, async/await patterns, dataclasses, dependency injection, logging configuration, and structured error handling.

Quality

84%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

77%

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

This is a solid, well-structured skill with excellent actionability through complete code examples and good workflow clarity with explicit validation loops. Its main weaknesses are moderate verbosity—some sections explain things Claude already knows (mutable defaults, bare excepts, PEP 8)—and referenced files that don't exist in the bundle, undermining the progressive disclosure design. Trimming obvious Python best practices and providing the referenced files would elevate this skill significantly.

Suggestions

Remove MUST DO/MUST NOT DO items that Claude already knows as a Python expert (e.g., 'don't use mutable default arguments', 'don't use bare except clauses', 'PEP 8 compliance') to improve conciseness.

Provide the five referenced files (references/type-system.md, references/async-patterns.md, etc.) or remove the reference table if they don't exist, as broken references reduce trust in the skill.

Consider removing or condensing the 'When to Use This Skill' and 'Knowledge Reference' sections, which largely restate information already conveyed by the skill's title, description, and content.

Dimension	Reasoning	Score
Conciseness	The skill is reasonably efficient but includes some unnecessary content. The 'When to Use This Skill' section largely restates what Claude would infer from context. The MUST DO/MUST NOT DO lists contain items Claude already knows (e.g., 'don't use mutable default arguments', 'don't use bare except'). The Knowledge Reference line at the bottom is just a keyword list adding little value. However, the code examples are well-chosen and not padded.	2 / 3
Actionability	The skill provides fully executable, copy-paste-ready code examples covering type-annotated functions, dataclasses with validation, async patterns, pytest fixtures with parametrize, and mypy configuration. Each example is complete and runnable, with specific commands for validation tools.	3 / 3
Workflow Clarity	The Core Workflow section provides a clear 5-step sequence with explicit validation checkpoints in step 5, including feedback loops: if mypy fails, fix and re-run; if tests fail, debug and iterate; if ruff/black reports issues, apply auto-fixes and re-validate. The mypy section also reinforces that errors must be resolved before proceeding.	3 / 3
Progressive Disclosure	The skill references five detailed reference files in a well-structured table with clear 'Load When' guidance, which is excellent design. However, no bundle files are provided, meaning none of these references actually exist. The main SKILL.md also includes substantial inline content (code examples, constraints) that could arguably be split out, making the file fairly long.	2 / 3
	Total	10 / 12 Passed

Description

92%

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 strong skill description that clearly articulates specific capabilities and provides explicit trigger guidance with both 'Use when' and 'Invoke for' clauses. It includes excellent natural trigger terms that developers would use. The main weakness is its broad scope covering many aspects of Python development, which could create overlap with other Python-focused skills.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: generates type-annotated code, configures mypy in strict mode, writes pytest test suites with fixtures and mocking, validates code with black and ruff, and covers dataclasses, dependency injection, logging configuration, and structured error handling.	3 / 3
Completeness	Clearly answers both 'what' (generates type-annotated Python code, configures mypy, writes pytest suites, validates with black/ruff) and 'when' with explicit triggers ('Use when building Python 3.11+ applications requiring type safety, async programming, or robust error handling' and 'Invoke for type hints, async/await patterns...').	3 / 3
Trigger Term Quality	Includes many natural keywords users would say: 'Python 3.11+', 'type hints', 'async/await', 'dataclasses', 'pytest', 'mypy', 'black', 'ruff', 'dependency injection', 'logging', 'error handling', 'type safety', 'async programming'. These are terms developers naturally use.	3 / 3
Distinctiveness Conflict Risk	While it specifies Python 3.11+ with type safety and async focus, it covers a broad range of Python development concerns (testing, linting, logging, error handling, dependency injection) that could overlap with general Python coding skills or testing-specific skills. The scope is wide enough to potentially conflict with other Python-related skills.	2 / 3
	Total	11 / 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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: Jeffallan/claude-skills
Commit: e8be415

Reviewed: 4 days ago

Table of Contents

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