ai-skills-python

Analyse functions in the code according to their correctness and collaboration

Analyse names and concepts in the code, looking for places the domain model and variable names could be clearer.

Write docstrings that document each function's contract. Identifies input invariants, errors raised on violation, errors from external state, and silenced errors from callees.

Generate property-based tests using Hypothesis. Builds input strategies in tests/strategies.py that model the valid search-space for each function, then writes minimal, behaviour-focused tests.

Perform mutation testing on the codebase. Introduces deliberate bugs one at a time, checks whether the test suite catches each one, and reports on test suite gaps. Optionally implements missing tests.

Use when writing or reviewing Python code layout — indentation, line length, blank lines, tabs vs spaces, continuation lines, binary operator breaks, source encoding. Invoke when user mentions "indentation", "line length", "blank lines", "code layout", "PEP 8 layout", or asks to format Python code structure.

Use when writing or reviewing Python comments and docstrings — block comments, inline comments, documentation strings, comment style. Invoke when user mentions "comments", "docstrings", "documentation", "PEP 8 comments", or asks about Python comment conventions.

Use when writing or reviewing Python import statements — ordering, grouping, absolute vs relative, wildcard avoidance, module-level dunder placement. Invoke when user mentions "imports", "import order", "import style", "PEP 8 imports", or asks about Python import organization.

Use when writing or reviewing Python naming conventions — modules, classes, functions, variables, constants, type variables, exceptions, public/internal interfaces. Invoke when user mentions "naming", "variable names", "class names", "PEP 8 naming", "snake_case", "CamelCase", or asks about Python naming conventions.

Use when writing or reviewing Python programming patterns — None comparisons, exception handling, return statements, type checking, boolean comparisons, sequence truthiness, string methods, context managers. Invoke when user mentions "PEP 8 programming", "best practices", "Python idioms", "exception handling", "comparisons", or asks about Pythonic code patterns.

Use for a full Python PEP 8 compliance review of a file or directory. Orchestrates all 9 PEP 8 skills (code-layout, imports, string-quotes, whitespace, trailing-commas, comments, naming, programming, type-annotations) to produce a consolidated report. Invoke when user asks to "review Python code", "PEP 8 audit", "check PEP 8 compliance", "lint for PEP 8", or "full PEP 8 review".

Use when writing or reviewing Python string quoting style — single vs double quotes, triple-quoted strings, avoiding unnecessary escapes. Invoke when user mentions "string quotes", "quote style", "triple quotes", "PEP 8 strings", or asks about Python string formatting conventions.

Use when writing or reviewing Python trailing comma usage — singleton tuples, multi-line collections, VCS-friendly formatting. Invoke when user mentions "trailing commas", "tuple comma", "PEP 8 commas", or asks about Python collection formatting.

Use when writing or reviewing Python type annotations — function annotations (PEP 484), variable annotations (PEP 526), annotation spacing, type checker directives. Invoke when user mentions "type hints", "annotations", "type annotations", "PEP 484", "PEP 526", "typing", or asks about Python type annotation formatting.

Use when writing or reviewing Python whitespace in expressions and statements — spacing around operators, inside delimiters, trailing whitespace, compound statements, annotation spacing. Invoke when user mentions "whitespace", "spacing", "operators", "PEP 8 whitespace", or asks about Python expression formatting.

Imagine future bug post-mortems for the codebase. Identifies fragile code, implicit assumptions, and likely failure modes by writing realistic incident reports for bugs that haven't happened yet.

Generate a condensed structural overview of a Python package or module — signatures, imports, class attributes, and docstrings only, with bodies replaced by ellipsis.

Analyze Python code and tighten type annotations. Finds missing attribute types, replaces loose dicts with Pydantic models, adds overloads, and removes redundant in-body annotations.

Audit try/except blocks for overly broad scope, by-catch risk, and catches of built-in exceptions that should be conditional checks. Tightens each block so the try covers only the operation that can actually fail.