Results for “acceptance-testing”

Acceptance Eval

Derives a comprehensive test plan and writes unit, integration, and end-to-end test cases from user stories and acceptance criteria, flagging issues in prior artifacts and declaring UAT readiness.

Generates structured Given/When/Then acceptance criteria for a user story or feature slice. Use when translating product requirements into testable scenarios that cover the happy path, edge cases, error states, and non-functional expectations for engineering handoff and QA.

UAT Sign-off

A/B and multivariate testing methodology. Design experiments, calculate sample sizes, determine statistical significance, avoid common pitfalls, and interpret results. Platform-agnostic framework applicable to landing pages, emails, ads, pricing, and product features. Use when the user asks about A/B testing, split testing, experiment design, statistical significance, or conversion experiments.

Generate red-phase acceptance test scaffolds using the TDD cycle. Use when the user says "lets write acceptance tests" or "I want to do ATDD"

Check post-launch adoption for a published ORD package and recommend iterate, graduate, or archive

Collects publicly available information about a target organization to identify attack surfaces, social engineering targets, technology stacks, and credential exposures for authorized security testing.

Provides a Flutter testing strategy covering unit, widget, integration, and BLoC tests with code examples, dependencies, and coverage commands.

Design and evaluate A/B tests with power, sample size, and robust metric interpretation. Use when: (1) planning controlled experiments, (2) reading p-values/effects, (3) sequential testing safeguards. NOT for: dark-pattern optimization.

Create user acceptance test journeys from a target user's perspective, with role-based scenarios, acceptance criteria, and evidence capture

Comprehensive web application testing patterns with Playwright selectors, wait strategies, and best practices

Walk a business/UAT approver through a plain-language demo of a verified feature and capture business acceptance signoff.

Write effective unit tests with best practices for any project. Use when writing tests, creating test cases, improving test coverage, increasing confidence before release, or when the user mentions testing. Mutation score / assertion theater → test-mutation.

Build reproducible ML experiment plans with hypotheses, metrics, and ablations. Use when: (1) planning experiments, (2) comparing variants, (3) defining acceptance thresholds. NOT for: long-running experiment execution.

Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write code.

Create comprehensive test scenarios from user stories with test objectives, starting conditions, user roles, step-by-step actions, and expected outcomes.