How does this skill help with large-scale refactors?

It uses a structured 'shim-first' workflow that leverages LSP to map all dependencies and references before moving code, preventing broken imports and runtime errors.

What is the benefit of using Protocols over hasattr checks?

Using Protocols (PEP 544) defines clear structural interfaces that Pyright can verify statically, making the code more predictable and easier to refactor compared to runtime attribute checks.

Why is Pyright used in this workflow?

Pyright acts as a contract baseline, identifying 'Optional' leaks or missing attributes immediately after a refactor step to ensure the code meets strict typing standards.

Can it handle dynamic imports?

Yes, the workflow specifically includes an inventory step for both standard and dynamic imports to ensure all module references are accounted for before any migration occurs.

Python LSP & Pyright Refactor

Name: Python LSP & Pyright Refactor
Author: shami-ah

byshami-ah

Desarrollo de API

Orchestrates complex Python code refactors using LSP and Pyright to ensure type safety and architectural integrity.

Acerca de

This skill provides a disciplined approach to non-trivial Python refactoring by leveraging Language Server Protocol (LSP) and Pyright diagnostics. It guides Claude through a 'shim-first' workflow, ensuring all definitions and references are inventoried before changes, maintaining stable public surfaces with re-exports, and using static analysis to eliminate type leaks. It is particularly effective for decoupling modules, hardening API boundaries with Protocols and TypedDicts, and executing large-scale structural changes without introducing regressions or 'Any' types.

Características Principales

LSP-driven symbol inventory and reference tracking
Systematic module migration with stable re-export wrappers
0 GitHub stars
Protocol-based interface definition to replace duck typing
Automated Pyright diagnostic checks for type safety
Internal refactoring plan execution using step-file ladders

Casos de Uso

Renaming core symbols and updating all references with compiler accuracy
Splitting large Python modules into smaller, more manageable sub-packages
Hardening API boundaries by replacing 'stringly typed' dicts with TypedDicts

Acerca de

Características Principales

LSP-driven symbol inventory and reference tracking
Systematic module migration with stable re-export wrappers
0 GitHub stars
Protocol-based interface definition to replace duck typing
Automated Pyright diagnostic checks for type safety
Internal refactoring plan execution using step-file ladders

Casos de Uso

Renaming core symbols and updating all references with compiler accuracy
Splitting large Python modules into smaller, more manageable sub-packages
Hardening API boundaries by replacing 'stringly typed' dicts with TypedDicts