Unit Testing

Essential graph algorithms including DFS, BFS, Dijkstra shortest path, and Union-Find with ready-to-use implementations.

Guide developers through property-based testing including property definition, shrinking, and framework-specific implementation

Jest unit testing standards covering configuration, test structure, testing patterns, and coverage requirements

Implement or extend a user-facing workflow in a web application, integrating with existing backend APIs. Use when the feature is primarily a UI/UX change backed by existing APIs, affects only the web frontend, and requires following design system, routing, and testing conventions.

Run credibility checks on feature interpretations including split-half stability and shuffle null tests

Orchestrate end-to-end feature development from requirements through implementation, testing, and review. Use when: (1) planning feature development stages, (2) coordinating multi-agent feature workflows, (3) understanding SDLC phases for new features.

Generates a rigorous experiment design given a hypothesis. Use when asked to design experiments, plan experiments, create an experimental setup, or figure out how to test a research hypothesis. Covers controls, baselines, ablations, metrics, statistical tests, and compute estimates.

Loop 3 of the Three-Loop Integrated Development System. CI/CD automation with intelligent failure recovery, root cause analysis, and comprehensive quality validation. Receives implementation from Loop 2, feeds failure patterns back to Loop 1. Achieves 100% test success through automated repair and theater validation. v2.0.0 with explicit agent SOPs.

Ability to design, analyse, test, and maintain mechanical systems and components that meet defined functional, safety, and performance requirements. Includes applying engineering principles to materials, structures, thermodynamics, fluid mechanics, and motion systems; producing and interpreting technical designs and specifications; validating designs through analysis and testing; and supporting manufacture, operation, and lifecycle management. Applies across industrial, infrastructure, energy, manufacturing, and product contexts and is independent of specific tools or industries, with human accountability retained for safety, compliance, and outcomes.

Find and debug errors using Docker Compose logs. Use proactively when tests fail or services misbehave. PRIMARY - docker compose logs --since 15m | grep -iE -B 10 -A 10 "error|fail|exception"

Laravel Dusk - Browser automation and testing API for Laravel applications. Use when writing browser tests, automating UI testing, testing JavaScript interactions, or implementing end-to-end tests in Laravel.

AI-driven development planning skill that produces TDD-ready specifications using research-backed methodologies (Plan-then-Act, Reflexion, ToT/LATS, ReAct).USE THIS SKILL PROACTIVELY when:- User requests a feature implementation- User reports a bug that needs fixing- User asks for code refactoring- Task involves multiple files or components- Requirements need clarification before coding- You need to create a comprehensive development planThis skill implements the complete planning pipeline: repo analysis → test-first design → structured plan generation → self-critique → TDD handover specification.OUTPUT: Structured TDD Handover Spec (JSON + Markdown) ready for TDD agent consumption.

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions

Vue 3 and Nuxt 3 development with TDD workflow, QA gates, and E2E test generation. Enforces unit testing before implementation, generates Playwright E2E tests from Gherkin acceptance criteria, and produces JSON reports.

Creates Claude Code Skills using a structured 6-phase workflow. Use when building skills, writing SKILL.md, designing skill architecture, or testing skill triggers. DO NOT use for general Claude Code docs or one-off tasks.

Validate code changes by intelligently selecting and running the appropriate test suites. Use this when editing code to verify changes work correctly, run tests, validate functionality, or check for regressions. Automatically discovers affected test suites, selects the minimal set of venvs needed for validation, and handles test execution with Docker services as needed.

Analyze, monitor, and improve CRAP (Change Risk Anti-Patterns) scores for untested complex code. Use when users want to: (1) Reduce technical debt and code risks, (2) Identify high-risk methods that need test coverage, (3) Validate CRAP thresholds for quality gates, (4) Generate coverage reports focused on complex methods, (5) Implement test coverage improvements to lower CRAP scores, or (6) Set up automated code quality monitoring based on CRAP metrics. **CRITICAL CONSTRAINT**: Code is in production and CANNOT be modified - CRAP reduction focuses ONLY on adding test coverage.

Implement feature steps using git worktrees, build and test adaptively, update implementation plan, and generate test plans. This skill should be used when ready to implement one or more steps from an implementation plan, automatically adapting to any framework, language, or project structure.

Core Python development skill for scripts, utilities, and general Python code. Covers uv package management, script dependencies, project setup, and coding standards. Use for Python file creation, running scripts, dependency management, or general Python tasks. For web APIs and servers, see python-backend skill. For testing, see python-testing skill.

Guidelines for preparing changelog entries for nextest releases following Keep a Changelog format