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name: implementing-python description: Implements concise, streamlined Python code matching exact architect specifications. Use when writing Python code, creating modules, or when the user asks to implement features in Python.

Python Implementation

Creates focused, streamlined Python implementations following architect specifications exactly. No over-engineering.

Python Standards

See docs/python-best-practices.md for comprehensive Python guidelines.

Workflow

1. Read architect specifications from provided documents
2. Validate scope - Simple (100-200 lines) vs Complex (500+ lines)
3. Study existing patterns in src/ structure
4. Implement minimal solution matching stated functionality
5. Run make validate_quick after writing code - fix formatting/type errors immediately
6. Create focused tests matching task complexity
7. Run make validate for full validation - fix all remaining issues

Implementation Strategy

Simple Tasks: Minimal functions, basic error handling, lightweight dependencies, focused tests

Complex Tasks: Class-based architecture, comprehensive validation, necessary dependencies, full test coverage

Always: Use existing project patterns, pass make validate

Output Standards

Simple Tasks: Minimal Python functions with basic type hints Complex Tasks: Complete modules with comprehensive testing All outputs: Concise, streamlined, no unnecessary complexity

Quality Checks

During development (after writing code):

Copymake validate_quick  # Fast check: formatting + types + complexity + tests

Before completing any task:

Copymake validate  # Full check: formatting + types + complexity + tests

CRITICAL: Run validation commands proactively during development. Fix issues immediately, don't wait until the end. All type checks, linting, complexity checks, and tests must pass before task completion.