What are the 'Naughtiness Levels' (L0-L8)?

They define the intensity of the testing, ranging from small valid inputs (L0) and boundary values (L1) to environment fault injection (L7) and coverage-guided exploration (L8).

What is the main benefit of combining PBT and Unit Testing?

Unit tests act as stable 'anchors' for core specifications, while PBT explores the vast input space for blind spots. When PBT finds a failure, it is shrunk and converted into a permanent unit test.

How does this skill handle discovered bugs?

It implements a counterexample workflow where failures discovered by PBT are minimized, recorded in a corpus, and added to the regression test suite to prevent future occurrences.

Is this skill compatible with existing frameworks?

Yes, it is designed to work with standard testing ecosystems (like pytest and Hypothesis) while following the Evidence-Led Development (ELD) methodology.

Systematic Test Design

Name: Systematic Test Design
Author: CAPHTECH

byCAPHTECH

0•

Security & Testing

Combines unit testing and property-based testing to systematically explore edge cases and secure software specifications.

This skill transforms the testing workflow by shifting the focus from manual test case enumeration to the structured design of properties and generators. It integrates seamlessly with Evidence-Led Development (ELD) to bridge the gap between abstract requirements (Laws/Terms) and concrete implementations. By escalating through eight progressive 'naughtiness' levels (L0-L8)—from basic valid inputs to complex fault injections—and capturing counterexamples as permanent regression assets, it ensures that discovered bugs are permanently neutralized and edge cases are thoroughly explored.

Key Features

010 GitHub stars

02ELD integration to verify business logic invariants and state-machine transitions.

03Escalating 'Naughtiness Ladder' (L0-L8) to adjust test intensity based on CI/CD cycles.

04Automated counterexample recovery for turning PBT failures into stable regression tests.

05Four-artifact workflow: Unit tests, property catalogs, generators, and counterexample corpora.

06Dual-mode testing integration of Unit Tests (specification anchors) and PBT (blind spot exploration).

Use Cases

01Scaling test intensity for complex state machines, concurrent systems, and API robustness.

02Designing comprehensive test suites for mission-critical business logic and financial calculations.

03Capturing and assets-izing edge cases discovered during random exploration for long-term stability.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add caphtech/claude-marketplace systematic-test-design

For use in Claude.ai and ChatGPT

Key Features

010 GitHub stars

02ELD integration to verify business logic invariants and state-machine transitions.

03Escalating 'Naughtiness Ladder' (L0-L8) to adjust test intensity based on CI/CD cycles.

04Automated counterexample recovery for turning PBT failures into stable regression tests.

05Four-artifact workflow: Unit tests, property catalogs, generators, and counterexample corpora.

06Dual-mode testing integration of Unit Tests (specification anchors) and PBT (blind spot exploration).

Use Cases

01Scaling test intensity for complex state machines, concurrent systems, and API robustness.

02Designing comprehensive test suites for mission-critical business logic and financial calculations.

03Capturing and assets-izing edge cases discovered during random exploration for long-term stability.