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dignified-python-313

Enforce dignified Python coding standards in the erk codebase.

Updated Aug 23, 2026
Search Tags:#code quality#refactoring#python#coding standards#type hints#code smells#python 3.13#LBYL
One-click install
npx skills add https://github.com/dagster-io/erk --skill dignified-python-313
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dignified-python-313
Source: https://github.com/dagster-io/erk/tree/main/packages/dot-agent-kit/src/dot_agent_kit/data/kits/dignified-python-313/skills/dignified-python
Command: npx skills add https://github.com/dagster-io/erk --skill dignified-python-313

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? This skill ensures your Python 3.13+ code adheres to advanced best practices and avoids production-tested code smells from Dagster Labs, reducing bugs and improving maintainability. It automates the enforcement of high-quality coding standards, freeing you from manual code reviews.

Core Features & Use Cases:

  • LBYL Exception Handling: Enforces proactive error checking (Look Before You Leap) over EAFP, leading to more predictable code.
  • Modern Type Syntax: Guides on Python 3.13+ type annotations (list[str], str | None), ensuring your code is future-proof and type-safe.
  • Dagster Code Smells: Identifies and helps refactor anti-patterns related to API design, parameter complexity, and class organization, based on real-world production experience.
  • Use Case: When reviewing a pull request, use this skill to automatically check for adherence to Python 3.13+ syntax, LBYL patterns, and common Dagster-identified code smells, providing precise, automated feedback to the developer.

Quick Start: Review the attached Python 3.13 code file 'my_new_feature.py' for adherence to dignified Python standards, specifically checking for LBYL patterns, modern type syntax, and any Dagster-identified code smells.

Frequently Asked Questions about dignified-python-313

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce LBYL error handling in Python 3.13 code?▼

LBYL (Look Before You Leap) error handling enforces proactive error checking before operations, replacing reactive exception handling. This skill automatically identifies and guides refactoring of EAFP patterns to LBYL, making code more predictable and reducing unexpected failures during development and code review.

What are modern Python 3.13 type hints and why should I use them?▼

Modern Python 3.13 type syntax uses built-in generics like `list[str]` and union operators like `str | None` instead of `List[str]` and `Optional[str]`. This skill ensures your annotations are future-proof, type-safe, and leverage Python 3.13+ capabilities for clearer, more maintainable code.

How can I identify and fix Dagster code smells in my Python project?▼

Dagster code smells are anti-patterns in API design, parameter complexity, and class organization identified from production experience. This skill automatically detects these patterns during code reviews and refactoring, providing precise feedback to improve code quality and maintainability.

Can I use this skill to review Python pull requests automatically?▼

Yes. This skill automates Python code review by checking pull requests against Python 3.13+ syntax standards, LBYL patterns, pathlib usage, type hints, and Dagster-identified code smells, providing instant feedback without manual inspection.

What coding standards does this skill enforce beyond type hints?▼

Beyond modern type syntax, this skill enforces pathlib for file handling, ABC interfaces for abstractions, absolute imports, explicit CLI boundaries, and production-tested Dagster Labs patterns for API design and parameter complexity management.

Does this skill work with existing Python codebases or only new code?▼

This skill applies to both writing and refactoring tasks, so it works with new code and existing Python codebases. It guides development across code edits within your project, making it suitable for both greenfield and legacy modernization efforts.

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