Python api consistency validator

Skill ArabelaTso/Skills-4-SE/skills/python-api-consistency-validator

A curated list of 180+ useful Claude Skills for Software Engineering and resources for customizing AI for SE workflows.

Install

npx -y skills add ArabelaTso/Skills-4-SE --skill python-api-consistency-validator

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Validate API consistency between two versions of Python libraries. Use when you need to compare API behavior, signatures, and exceptions between library versions to identify breaking changes, incompatible modifications, and behavior differences. The skill performs static analysis of Python code, compares function signatures, class definitions, parameter types, return types, and generates a detailed JSON report with breaking changes, warnings, and migration guidance. Supports Python libraries and packages.

SKILL.md

2.4 KB, as published. Nobody here has run it

Python API Consistency Validator

Overview

This skill validates API consistency between two versions of Python libraries by comparing signatures, behavior, and exceptions. It identifies breaking changes, incompatible modifications, and provides detailed reports to guide safe API migration or upgrade.

Quick Start

# Compare two versions of a Python library
python scripts/validate.py /path/to/old_version /path/to/new_version

# Specify output file
python scripts/validate.py old_lib/ new_lib/ --output report.json

What Gets Validated

Function Signatures - Parameters, return types, decorators
Class Definitions - Methods, inheritance, attributes
Parameter Changes - Added, removed, or modified parameters
Return Type Changes - Modified return types
Removed APIs - Deleted functions, classes, or methods

Validation Report

The tool generates a JSON report with:

Breaking Changes: API removals, incompatible modifications
Warnings: Type changes, signature modifications
Info: New additions, non-breaking changes
Summary: Total issues by severity

Example report:

{
  "summary": {
    "breaking_changes": 3,
    "warnings": 5,
    "info": 2
  },
  "breaking_changes": [
    {
      "type": "function_removed",
      "name": "deprecated_func",
      "severity": "breaking",
      "message": "Function 'deprecated_func' was removed"
    }
  ]
}

Usage

python scripts/validate.py <old_version_path> <new_version_path> [--output <report.json>]

The validator exits with code 1 if breaking changes are found, 0 otherwise.

Tips

Run validation before upgrading dependencies
Review breaking changes carefully
Check warnings for potential issues
Use in CI/CD pipelines to catch API changes
Compare against semantic versioning expectations

Gives 0 of the 12 instructions most quality gates skills give

Counted across 1,195 of the 2,094 authors here whose files we hold, read 2026-08-06

read the output and check the exit codein 55 of 1195, across 14 files
verify requirements using a line-by-line checklistin 53 of 1195, across 12 files
identify the verification command proving the claimin 53 of 1195, across 12 files
run the full verification commandin 51 of 1195, across 11 files
verify output confirms the claimin 49 of 1195, across 10 files
check version control diff after agent delegationin 45 of 1195, across 5 files
state claim with evidencein 43 of 1195, across 3 files
run the test suitein 32 of 1195, across 24 files
keep state in memory by defaultin 27 of 1195, across 6 files
make prototype runnable with one commandin 26 of 1195, across 5 files
detect the package manager from lockfilesin 24 of 1195, across 5 files
produce a verification reportin 23 of 1195, across 12 files

Said here and by no other author read

compare two versions of a python library
validate function signatures parameters and return types
validate class definitions methods and inheritance
identify removed or modified apis
specify an output file for the report
run validation before upgrading dependencies

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.