Testing & QA skills

Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing.

Estrategias de pruebas Python usando pytest, metodología TDD, fixtures, mocking, parametrización y requisitos de cobertura.

React component testing with React Testing Library, Vitest/Jest, MSW for network mocking, accessibility assertions with axe, and the decision boundary between component tests and Playwright/Cypress end-to-end runs. Use when writing or fixing tests for React components, hooks, or pages.

Patrones de pruebas E2E con Playwright, Page Object Model, configuración, integración CI/CD, gestión de artefactos y estrategias para pruebas inestables.

Bucle de verificación para proyectos Laravel: verificaciones de entorno, linting, análisis estático, pruebas con cobertura, escaneos de seguridad y preparación para despliegue.

Desarrollo guiado por pruebas para Spring Boot usando JUnit 5, Mockito, MockMvc, Testcontainers y JaCoCo. Usar al agregar funcionalidades, corregir bugs o refactorizar.

Patrones de pruebas Kotlin con Kotest, MockK, pruebas de coroutines, pruebas basadas en propiedades y cobertura con Kover. Sigue la metodología TDD con prácticas idiomáticas de Kotlin.

Bucle de verificación para proyectos Spring Boot: build, análisis estático, pruebas con cobertura, escaneos de seguridad y revisión de diff antes del lanzamiento o PR.

Patrones de pruebas en Rust incluyendo pruebas unitarias, de integración, async, basadas en propiedades, mocking y cobertura. Sigue la metodología TDD.

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Bucle de verificación para proyectos Quarkus: build, análisis estático, pruebas con cobertura, escaneos de seguridad, compilación nativa y revisión de diff antes del lanzamiento o PR.

Patrones de pruebas Go incluyendo pruebas basadas en tablas, subpruebas, benchmarks, fuzzing y cobertura de código. Sigue la metodología TDD con prácticas idiomáticas de Go.

Framework formal de evaluación para sesiones de Claude Code que implementa principios de desarrollo orientado a evals (EDD)

Sistema de verificación completo para sesiones de Claude Code.

Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs.

Desarrollo guiado por pruebas para Quarkus 3.x LTS usando JUnit 5, Mockito, REST Assured, pruebas Camel y JaCoCo. Usar al agregar funcionalidades, corregir bugs o refactorizar servicios orientados a eventos.

Usar este skill al escribir nuevas funcionalidades, corregir bugs o refactorizar código. Aplica el desarrollo guiado por pruebas con 80%+ de cobertura incluyendo pruebas unitarias, de integración y E2E.

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

Hyperliquid market data, account history, trade review.

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Execute plans via delegate_task subagents (2-stage review).

4-phase root cause debugging: understand bugs before fixing.

Debug Python: pdb REPL + debugpy remote (DAP).

Exploratory QA of web apps: find bugs, evidence, reports.

Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.

Roleplay the most difficult, tech-resistant user for your product. Browse the app as that persona, find every UX pain point, then filter complaints through a pragmatism layer to separate real problems from noise. Creates actionable tickets from genuine issues only.

TDD: enforce RED-GREEN-REFACTOR, tests before code.

DSPy: declarative LM programs, auto-optimize prompts, RAG.

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Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.

Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.

Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one. Triggers on "ideate", "refine this idea", or "stress-test my plan".

Review RTK Rust code for idiomatic simplification. Detects over-engineering, unnecessary allocations, verbose patterns. Applies Rust idioms without changing behavior.

TDD workflow for RTK filter development. Red-Green-Refactor with Rust idioms. Real fixtures, token savings assertions, snapshot tests with insta. Auto-triggers on new filter implementation.

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Perform thorough code reviews with security, performance, and maintainability analysis. Use when user asks to review code, check for bugs, or audit a codebase.

Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.

Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent

Agent skill for researcher - invoke with $agent-researcher

Agent skill for tester - invoke with $agent-tester

Agent skill for coder - invoke with $agent-coder

Agent skill for worker-specialist - invoke with $agent-worker-specialist

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.

Replay a recorded session trajectory against the same URL or a mutated variant; uses browser-selectors embedding similarity to recover from DOM drift

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Agent skill for refinement - invoke with $agent-refinement

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Agent skill for sparc-coordinator - invoke with $agent-sparc-coordinator

Agent skill for tdd-london-swarm - invoke with $agent-tdd-london-swarm

Agent skill for test-long-runner - invoke with $agent-test-long-runner

Agent skill for implementer-sparc-coder - invoke with $agent-implementer-sparc-coder

15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.

UI test recipe -- composes browser-record (capture) + browser-replay (verify) so every test produces a replayable RVF artifact, not an ephemeral run

Agent skill for orchestrator-task - invoke with $agent-orchestrator-task

Agent skill for production-validator - invoke with $agent-production-validator