implementation-design-patterns-python

implementation-design-patterns-python is a Design patterns & component architecture skill for AI agents, published by pproenca in the dot-skills repository on GitHub. Skillspace rates implementation-design-patterns-python C (71/100) and it passed the safety scan; the rating is based on static analysis only.

Implementation guide for the 22 Gang of Four design patterns in idiomatic modern Python (3.10+), distilled from refactoring.guru. Use when writing, refactoring, or reviewing Python with a pattern-shaped problem — class-explosion from inheritance, conditionals switching on type, tight coupling to concrete classes, tree-shaped models, runtime algorithm selection, undo/redo, state-dependent behavior, or hiding subsystem complexity. Each entry leads with the Pythonic form (functions, dataclasses, Protocol, singledispatch, match, generators, copy/replace) and falls back to the class-based GoF structure only when identity, state, or dispatch require it. Includes intent, applicability (when to use AND when NOT to), a runnable example, steps, pros/cons, and relations. Trigger even when no pattern is named — cues like "too many constructor params," "giant if/elif," "swap behavior at runtime," "need undo," or "walk a tree" are pattern-shaped. Covers all 5 Creational, 7 Structural, and 10…

Grade
C
Quality
71 / 100
Safety
Passed
GitHub stars
180

Unproven: rated by static analysis only, not yet compared head-to-head.

Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it is a near-duplicate variant of another skill. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided

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Our review

Architecture
94 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

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