testing-python

Create and correct Python tests from story specifications.

1|Updated Jan 6, 2026

Search Tags:#testing #pytest #python #unit-testing #hypothesis #test-writing #test-fixing

Ready to run

npx skills add https://github.com/outcomeeng/claude --skill testing-python-outcomeeng

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: testing-python
Source: https://github.com/outcomeeng/claude/tree/main/plugins/python/skills/testing-python
Command: npx skills add https://github.com/outcomeeng/claude --skill testing-python-outcomeeng

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Writing and maintaining Python tests is error-prone; this skill ensures tests are created and fixed as part of story development, preventing silent test gaps.

Core Features & Use Cases

WRITE mode creates new tests from a story specification and related context.
FIX mode reads reviewer feedback, patches failing tests, and re-runs tests.
Supports property-based tests for parsers/serializers using Hypothesis.
Enforces type hints, explicit constants, and dependency-injection patterns to avoid mocks.

Quick Start

Provide the path to a story spec to begin writing or fixing Python tests.

Frequently Asked Questions about testing-python

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

FAQPage Schema

How do I automate writing Python tests from a story specification?▼

You can automate Python test creation by providing a path to a story specification, triggering WRITE mode to generate new tests while enforcing typing, test structure standards, and property-based testing.

What is the best way to fix failing pytest tests and address reviewer feedback?▼

The best way to fix failing pytest tests is using a FIX mode that reads reviewer feedback, patches the failing tests, and re-runs the tests to verify corrections against the story specification.

Does property-based testing with Hypothesis work for Python parsers and serializers?▼

Property-based testing with Hypothesis works for Python parsers and serializers by generating test cases that validate structural invariants, supported within standard test guidelines for story development.

How do I structure Python unit tests to avoid mocks and enforce dependency injection?▼

Structuring Python unit tests to avoid mocks involves enforcing type hints, explicit constants, and dependency-injection patterns within the test generation process to ensure tests are created and fixed correctly.

Why do my Python tests have silent gaps during story development?▼

Python tests develop silent gaps during story development when test creation and correction are not automated, allowing errors in test structure, typing, and property-based testing standards to go unnoticed.