python
Python development guidelines and best practices. Use when working with Python code.
65
Does it follow best practices?
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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.
This description is too vague and generic to effectively guide skill selection. While it includes a 'Use when' clause, both the capabilities ('guidelines and best practices') and trigger conditions ('working with Python code') are overly broad. The description would likely conflict with any other Python-related skill and doesn't help Claude understand what specific actions this skill enables.
Suggestions
Replace 'guidelines and best practices' with specific concrete actions (e.g., 'Enforces PEP 8 style, configures type hints, structures modules, sets up virtual environments').
Narrow the 'Use when' clause to specific scenarios (e.g., 'Use when setting up new Python projects, reviewing code style, or asking about Python conventions').
Add distinguishing trigger terms that differentiate this from other Python skills (e.g., 'code style', 'PEP 8', 'project structure', 'conventions', 'linting').
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses vague language like 'guidelines and best practices' without listing any concrete actions. It doesn't specify what actions Claude will perform (e.g., formatting, linting, type hints, testing). | 1 / 3 |
Completeness | Has a weak 'what' (guidelines and best practices) and includes a 'Use when' clause, but the 'when' is overly broad ('working with Python code') and the 'what' lacks specificity about actual capabilities. | 2 / 3 |
Trigger Term Quality | Includes 'Python' and 'Python code' which are natural terms users would say, but misses common variations like '.py files', 'scripts', 'modules', 'packages', or specific Python concepts. | 2 / 3 |
Distinctiveness Conflict Risk | 'Working with Python code' is extremely broad and would conflict with any Python-related skill (testing, debugging, refactoring, documentation, etc.). No clear niche is established. | 1 / 3 |
Total | 6 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured Python guidelines document that efficiently communicates standards without unnecessary verbosity. Its main weakness is the lack of concrete code examples to illustrate patterns like dependency injection, Protocol usage, and Pydantic models, which would make the guidance more immediately actionable.
Suggestions
Add a brief executable code example showing the Protocol-based dependency injection pattern
Include a concrete Pydantic v2 model example demonstrating the expected data model style
Add a small example showing the expected environment.py structure with individual accessor methods
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, presenting guidelines without explaining basic Python concepts Claude already knows. Every section delivers actionable standards without padding or unnecessary context. | 3 / 3 |
Actionability | Provides specific guidance (use Pydantic v2, pytest, AAA pattern) but lacks executable code examples. Guidelines like 'use Protocol classes' and 'dependency injection' would benefit from concrete code snippets showing the expected patterns. | 2 / 3 |
Workflow Clarity | The Implementation section mentions checking tests and type checking before committing, but lacks explicit validation steps or a clear workflow sequence. For a guidelines document, the process of applying these standards could be more explicitly sequenced. | 2 / 3 |
Progressive Disclosure | Well-organized with clear sections and appropriate references to external files (uv-scripts.md, uv-monorepo.md) for specialized topics. Content is appropriately scoped for a SKILL.md overview without being monolithic. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%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.
- Reviewed
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