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Found 23 Skills
Python and wxPython development reference patterns, common pitfalls, framework-specific guides, desktop accessibility APIs, and cross-platform considerations. Use when building, debugging, packaging, or reviewing Python desktop applications.
Language-specific verification for Python, TypeScript/JavaScript, and Go. Checks type safety, language idioms, and best practices. Use when asked to "verify language", "check types", or for language-specific checks.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
Simplifies and refines Python code for clarity, consistency, and maintainability while preserving all functionality. Applies dignified-python standards. Focuses on recently modified code unless instructed otherwise.
Comprehensive Python programming guidelines based on Google's Python Style Guide. Use when you needs to write Python code, review Python code for style issues, refactor Python code, or provide Python programming guidance. Covers language rules (imports, exceptions, type annotations), style rules (naming conventions, formatting, docstrings), and best practices for clean, maintainable Python code.
Python best practices for writing production-grade code. This skill should be used when writing, reviewing, or refactoring Python code. Triggers on tasks involving Python development, error handling patterns, dictionary operations, and code quality improvements.
Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.
Senior Python developer. Use when writing, reviewing, or refactoring Python code. Enforces idiomatic Python, type hints, and modern patterns.
Python coding standards with automatic version detection. Use when writing, reviewing, or refactoring Python to ensure adherence to LBYL exception handling patterns, modern type syntax (list[str], str | None), pathlib operations, ABC-based interfaces, absolute imports, and explicit error boundaries at CLI level. Also provides production-tested code smell patterns from Dagster Labs for API design, parameter complexity, and code organization. Essential for maintaining erk's dignified Python standards.
Complete Python gotchas reference. PROACTIVELY activate for: (1) Mutable default arguments, (2) Mutating lists while iterating, (3) is vs == comparison, (4) Late binding in closures, (5) Variable scope (LEGB), (6) Floating point precision, (7) Exception handling pitfalls, (8) Dict mutation during iteration, (9) Circular imports, (10) Class vs instance attributes. Provides: Problem explanations, code examples, fixes for each gotcha. Ensures bug-free Python code.
Refactor Django/Python code to improve maintainability, readability, and adherence to best practices. Transforms fat views, N+1 queries, and outdated patterns into clean, modern Django code. Applies Python 3.12+ features like type parameter syntax and @override decorator, Django 5+ patterns like GeneratedField and async views, service layer architecture, and PEP 8 conventions. Identifies and fixes anti-patterns including mutable defaults, bare exceptions, and improper ORM usage.