| name | code-quality |
| description | Python code-quality anti-patterns and review checks: exception-hierarchy correctness, singleton identity comparison, narrow exception handling, wildcard-import avoidance, magic-number naming, and dead-local removal. Use when reviewing or self-reviewing Python code for correctness and readability defects that linters and reviewers should catch. |
| user-invocable | false |
| disable-model-invocation | true |
| version | 1.0.0 |
| updated | 2026-06-15 |
| category | toolchain |
| author | Claude MPM Team |
| license | MIT |
| progressive_disclosure | {"entry_point":{"summary":"Catch high-value Python code-quality anti-patterns in review: malformed exception classes, == None vs is None, bare except, wildcard imports, magic numbers, unused locals","when_to_use":"When reviewing or self-reviewing Python code for correctness/readability defects, configuring ruff/pylint rules, or writing code-quality guidance — not for testing mechanics (use pytest) or whole-codebase scoring (use code-quality-scoring)","quick_start":"1. Ensure custom exceptions derive from Exception 2. Compare None/True/False with is, not == 3. Catch the narrowest exception you can handle, never bare except 4. Replace wildcard imports with explicit names 5. Name magic numbers as constants 6. Remove unused locals — enforce all six with ruff/pylint/mypy in CI"},"references":["quality-antipatterns.md"]} |
| context_limit | 600 |
| tags | ["python","code-quality","anti-patterns","code-review","pep8","ruff","pylint","static-analysis"] |
| requires_tools | [] |
Python Code Quality
High-value Python code-quality anti-patterns to check during review or self-review.
This skill is review-focused: it covers correctness and readability defects that a
reviewer (or a linter) should flag, separate from testing mechanics (pytest) and
whole-codebase health scoring (code-quality-scoring).
Source note: These anti-patterns are derived from CAST Highlight's Python code
quality indicators (https://doc.casthighlight.com/), which reference PEP 8 and the
Python data model as primary sources. Where a rule mirrors PEP 8, the PEP is the
authoritative source. All examples are original.
When to Use This Skill
Use it when the task is "is this Python code clean and correct?" — for example:
- Reviewing a pull request and checking for the defects below.
- Self-reviewing before opening a PR.
- Configuring
ruff/pylint/mypy rules so CI catches these automatically.
- Writing or updating a team's Python code-quality guidance.
Do not use it for testing mechanics (use the pytest skill) or for scoring a whole
codebase's health and technical debt (use the code-quality-scoring skill).
Core Anti-Patterns (Summary)
Six highest-value Python anti-patterns. Each has a non-compliant/compliant example and a
"how to test" note in the reference doc:
- Custom exceptions must derive from
Exception — a class meant to be raised that
inherits from object fails at runtime and breaks every except clause.
- Compare singletons with
is, not == — use is/is not for None/True/False
(PEP 8); use is only for singletons, never for value comparison.
- Avoid bare / overly broad
except — catch the narrowest type you can handle; a
generic except Exception only as a last-position fallback that logs or re-raises.
- Avoid wildcard imports (
from x import *) — they hide dependencies, risk silent
name collisions, and defeat static analysis.
