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test-standards

Document Python testing standards for pytest, Hypothesis, and snapshots.

1|Updated Dec 22, 2025
Search Tags:#automation#testing#pytest#fixtures#unit-testing#hypothesis#snapshot-testing
One-click install
npx skills add https://github.com/CybLow/pypaginate --skill test-standards-cyblow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: test-standards
Source: https://github.com/CybLow/pypaginate/tree/main/.opencode/skills/test-standards
Command: npx skills add https://github.com/CybLow/pypaginate --skill test-standards-cyblow

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Testing standards documentation is frequently inconsistent across projects, leading to fragile tests, onboarding friction, and slower delivery.

Core Features & Use Cases

  • Comprehensive conventions for test naming (test_<unit><scenario><expected>), AAA structure, and marker usage to improve readability and filtering.
  • Detailed guidance on test organization, fixtures, factories, mocking strategies, property-based testing with Hypothesis, snapshot testing, and async testing to improve reliability and coverage.
  • Clear workflows and anti-pattern guidance to accelerate onboarding and maintainability across Python projects.

Quick Start

Create a pytest-based project template and apply the prescribed naming, structure, and coverage guidelines to ensure consistent testing practices across modules.

Frequently Asked Questions about test-standards

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

FAQPage Schema
How do I standardize pytest naming conventions and AAA structure across Python projects?▼

Establish pytest testing standards by enforcing structured AAA sections, specific naming conventions, and marker usage. This ensures consistent test organization, coverage targets, and reliable execution across Python projects.

What is the best way to document fixtures and mocking strategies for Python unit testing?▼

Document fixtures and mocking strategies by defining clear workflows and anti-pattern guidelines for Python unit testing. This accelerates onboarding and maintains reliability by ensuring consistent test organization across modules.

How do I configure Hypothesis property-based testing and snapshot testing standards?▼

Configure Hypothesis property-based testing and snapshot testing by documenting detailed guidance within your testing standards. This defines advanced testing workflows, recommended organization, and coverage targets for Python projects.

What testing anti-patterns should I avoid when setting up pytest project standards?▼

Avoid testing anti-patterns by following clear workflow guidance that identifies fragile practices. Establishing pytest standards helps prevent inconsistent test documentation, onboarding friction, and slower delivery across Python projects.

Does this testing standard require YAML frontmatter for Python test documentation?▼

Yes, the testing standard enforces YAML frontmatter requirements alongside structured sections for Python test documentation. This enforces recommended organization, coverage targets, and anti-pattern guidelines to maintain consistency.

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