Does this skill remove code immediately?

No, it follows a gradual deprecation strategy, marking code as deprecated first and providing a clear migration path before total removal in a future major version update.

Why is backward compatibility emphasized in this pattern?

Sudden removal of dependencies can break production workflows; this skill ensures users receive actionable warnings and are given time to transition to new implementations without downtime.

What is the main goal of the Dependency Deprecation skill?

It provides a structured pattern to remove external dependencies from a project while ensuring the software remains functional for legacy users through gradual deprecation and warnings.

Which project files are typically affected by this workflow?

The workflow covers source code (.py), configuration files (pyproject.toml, envs/*.yml), and all relevant documentation (README, guides, and historical docs).

Dependency Deprecation Pattern

Name: Dependency Deprecation Pattern
Author: smith6jt-cop

bysmith6jt-cop

Developer Tools

Implements a standardized workflow for phasing out software dependencies while ensuring backward compatibility and smooth user migrations.

About

This skill provides a comprehensive framework for managing the deprecation of external dependencies, such as Java, Maven, or legacy libraries, within a software project. It guides Claude through a verified six-step process: identifying code touchpoints, implementing Pythonic deprecation warnings, updating dependency checkers, modifying project configuration files like pyproject.toml, and refreshing documentation. By following this pattern, developers can effectively reduce technical debt and installation friction without breaking existing user workflows or causing silent failures during transitions to newer implementations.

Key Features

Verified migration path testing to ensure dual-compatibility during transitions
Automated identification of dependency touchpoints across source code and configurations
Configuration management for pyproject.toml and conda environment files
0 GitHub stars
Documentation update patterns for historical and core project files
Standardized implementation of Python DeprecationWarnings and fallback logic

Use Cases

Phasing out legacy GPU backends in favor of modern libraries like CuPy or PyTorch
Replacing heavy Java/Maven dependencies with lightweight Python-native alternatives
Consolidating project install requirements by moving mandatory dependencies to optional groups

About

Key Features

Verified migration path testing to ensure dual-compatibility during transitions
Automated identification of dependency touchpoints across source code and configurations
Configuration management for pyproject.toml and conda environment files
0 GitHub stars
Documentation update patterns for historical and core project files
Standardized implementation of Python DeprecationWarnings and fallback logic

Use Cases

Phasing out legacy GPU backends in favor of modern libraries like CuPy or PyTorch
Replacing heavy Java/Maven dependencies with lightweight Python-native alternatives
Consolidating project install requirements by moving mandatory dependencies to optional groups