Discipline for applying test-driven development where it adds regression value — preflight the change, reuse usable project test infrastructure, then red-green-refactor. Use before implementing features or fixing bugs to decide whether TDD applies, when practicing TDD, introducing project-appropriate testing for current work, or reviewing whether work was actually test-driven.
Test web applications with screen readers including VoiceOver, NVDA, and JAWS. Use when validating screen reader compatibility, debugging accessibility issues, or ensuring assistive technology support.
iOS testing with XCTest/XCUITest on simulators and devices: layered strategy, determinism/flake control, device matrix selection, CI ergonomics, and repeatable simulator automation.
Discipline for applying test-driven development where it adds regression value — preflight the change, reuse usable project test infrastructure, then red-green-refactor. Use before implementing features or fixing bugs to decide whether TDD applies, when practicing TDD, introducing project-appropriate testing for current work, or reviewing whether work was actually test-driven.
Use this agent when you need to analyze data patterns, build predictive models, or extract statistical insights from datasets. Invoke this agent for exploratory analysis, hypothesis testing, machine learning model development, and translating findings into business recommendations. Specifically:\n\n<example>\nContext: Product team wants to understand why customer churn increased 15% last month and identify actionable retention levers.\nuser: "We're seeing higher churn recently. Can you analyze our customer data and tell us what's driving it?"\nassistant: "I'll conduct a comprehensive exploratory analysis to identify churn patterns, then build a predictive model to rank the most influential factors. I'll deliver both statistical findings and business recommendations for retention strategies."\n<commentary>\nUse this agent when you have a business question tied to data. The agent will perform EDA, identify significant patterns, and translate statistical findings into actionable business insights backed by rigorous methodology.\n</commentary>\n</example>\n\n<example>\nContext: Data engineering team has prepared a new dataset with user behavior logs. The product manager wants to forecast demand for the next quarter.\nuser: "We have three months of behavioral data. Can you build a forecast model for next quarter demand?"\nassistant: "I'll analyze temporal patterns, decompose trends and seasonality, test multiple forecasting approaches (ARIMA, Prophet, neural networks), and deliver a probabilistic forecast with confidence intervals plus recommendations for demand planning."\n<commentary>\nInvoke this agent when you need predictive modeling on time series data. The agent will select appropriate statistical methods, validate assumptions, and deliver forecasts with quantified uncertainty.\n</commentary>\n</example>\n\n<example>\nContext: A/B test results are ready. Product team ran a pricing experiment and needs guidance on whether the results are statistically significant and if they should ship the change.\nuser: "We ran an A/B test on pricing. Can you analyze if the results are real and what we should do?"\nassistant: "I'll perform hypothesis testing on your treatment vs. control groups, check statistical significance (p-value, effect size), assess for multiple comparison issues, calculate business impact (ROI, revenue lift), and provide a clear recommendation backed by rigorous statistical analysis."\n<commentary>\nUse this agent when you have experimental or A/B test results requiring statistical validation and business impact assessment. The agent will verify statistical rigor and translate p-values into business decisions.\n</commentary>\n</example>
Write and run acceptance tests with axx, black-box against services (REST and OpenAPI, WireMock, SQL, MongoDB, Kafka, logs, files, web apps in real browsers, cloud services). Use when turning acceptance criteria into .feature files, adding scenarios, or editing axx.yaml.
Implementation workflow for maintaining and extending the Cytology Test Result form (forms/cytology-test-result/) — editing its spec, schema, or engine, regenerating derived artefacts, and running its verify gates. Use when implementing a change to this form's spec, SQL schema, front-end, back-end, or personas. For the repo-wide workflow, use form-examples-maintainer-skill instead.
Review Playwright tests for quality. Use when user says "review tests", "check test quality", "audit tests", "improve tests", "test code review", or "playwright best practices check".
Generate comprehensive unit tests for Next.js 16 applications covering App Router, Server Components, Client Components, API routes, and Server Actions with industry best practices
Open-source data quality tool: profiles tables, generates data quality tests from the profiling results, and runs them on a schedule with freshness, volume, and schema monitoring. Web UI, REST API, and MCP server. 14 databases plus CSV, Parquet, and JSON files. Apache 2.0.
This skill enables testing in the domain of category-theory (mathematics). It represents advanced-level expertise and is designed for production use in research, industry, and educational contexts.
This skill enables testing in the domain of optogenetics (neuroscience). It represents intermediate-level expertise and is designed for production use in research, industry, and educational contexts.
This skill enables testing in the domain of optogenetics (neuroscience). It represents intermediate-level expertise and is designed for production use in research, industry, and educational contexts.