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readable-py

Readable Python code rules inspired by The Art of Readable Code. Use when writing, reviewing, or refactoring Python code. Enforces short functions, flat control flow, clear naming, readable structure, and Pythonic idioms.

68

Quality

82%

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SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

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

A well-structured, concise, and actionable ruleset with executable examples and clear sectioning. Its only weakness is that all content is inlined with no external references, leaving modest room for progressive disclosure of the longer Python-specific rules.

Suggestions

Consider extracting the Python-specific rules (sections 15-19) into a references file linked from the body, keeping the core readability rules as the lean overview.

Tighten a few elaborated bullets (e.g. section 14) to single-line directives to push conciseness toward the leanest anchor.

Add one or two complete runnable example functions alongside the illustrative snippets to make the guidance fully copy-paste ready.

DimensionReasoningScore

Conciseness

Lean bullet rules that assume Claude's competence with no padding about basic Python concepts; a few sections elaborate slightly more than necessary, keeping it just short of the leanest anchor.

4 / 5

Actionability

Concrete directive rules paired with executable code examples (nested loops, comprehensions, dataclasses, pathlib, formatter chains); examples are illustrative snippets rather than full programs, leaving minor gaps.

4 / 5

Workflow Clarity

A single-purpose rules/reference skill with an unambiguous application; the simple-skill exception applies and no destructive or batch operations require validation checkpoints.

5 / 5

Progressive Disclosure

Well-organized into clearly headed numbered sections with no nested references; content is all inline (~213 lines) with the Python-specific block that could optionally be split into a reference file.

4 / 5

Total

17

/

20

Passed

Description

83%Weight 40%Scale 1-5

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

A strong description that clearly states what it enforces and when to use it, with concrete user-language triggers. It is specific, complete, and distinct, with only minor gaps in trigger synonym coverage.

DimensionReasoningScore

Specificity

Lists several concrete enforcement areas ('short functions, flat control flow, clear naming, readable structure, and Pythonic idioms') plus the application contexts (writing, reviewing, refactoring), with only minor coverage gaps.

4 / 5

Completeness

Explicitly answers both what it does (enforces the listed readability rules) and when to use it ('Use when writing, reviewing, or refactoring Python code') with concrete triggers.

5 / 5

Trigger Term Quality

Natural user-language phrases like 'writing, reviewing, or refactoring Python code' and 'Pythonic idioms' are present, though a few synonyms (e.g. 'clean code', 'lint', 'PEP 8') are missing.

4 / 5

Distinctiveness Conflict Risk

Clearly niched to readable-Python guidance with distinct triggers; minor overlap risk with general linting/formatting skills.

4 / 5

Total

17

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
crazyguitar/pysheeet
Reviewed

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