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SkillsMP has collected 14 skills from devclarityai/qa-environment-setup. Open a skill to review its source and details.
Showing 14 of 14 collected skills.
Verify and repair the local environment for Playwright-based QA training - node and npm, repo dependencies, browser binaries, playwright-cli, the Playwright MCP server, and .playwright.env - then prove it works with one smoke test. Covers macOS, Windows…
Guides the creation of Playwright API tests from exploration through implementation. Covers API discovery, test plan creation, helper/data factory development, and test writing with human checkpoints at each stage.
Analyze a test automation codebase and produce a single-page HTML "model of what exists" report covering assertion depth, test levels, run mechanics, environments, test data, authentication, network handling, dependencies and security, run commands, locators…
Guides the creation of Playwright E2E tests from planning through implementation. Covers test plan creation, data seeding, Page Object Model development, and test writing with human checkpoints at each stage.
Generates exploratory test scenarios that go beyond ticket requirements. Uses playwright-cli for live browser exploration to surface system-wide impacts testers would otherwise miss. Supports two modes — explore from a prompt or from a ticket (Jira/Linear ID).
Explores features to discover stable locators and fixes broken locators in Playwright tests. Two modes — explore (proactive discovery) and fix (reactive repair) — both using playwright-cli for live browser interaction.
Automate browser interactions, test web pages and work with Playwright tests.
Reads a ticket's acceptance criteria and surfaces gaps, ambiguity, unstated assumptions, and missing cases - then ranks what to test by risk (severity x priority). Use before writing any tests, to interrogate the spec. Day 1 acceptance-criteria + risk block…
Drafts a structured, reproducible bug report from behavior observed in the running app. Use after a tester reproduces a defect and wants a clean report another tester could file without a follow-up conversation. Day 2 bug-reporting block of the QA…
Builds the context an AI needs to test an app well - product/area notes and user personas - and writes them into a reusable reference file. Use to turn a thin, generic AI run into a grounded one. Day 1 context live-build of the QA Foundational training.
Takes an existing set of test cases for a feature and returns what is missing - uncovered states, boundaries, negative paths, and unstated rules. Use when inheriting a test suite or auditing coverage. This is road 2 of the QA Foundational Day 2 "five roads."
Turns markdown or QA skill output into a simple, consistently styled standalone HTML report. Saves it to a qa-reports folder on the Desktop and opens it in the default browser. Works on Mac and Windows. Use when output from a qa-xxx skill (AC analysis, bug…
Turns a feature input (ticket + acceptance criteria, existing cases, a screenshot, observed app behavior, or a recorded walkthrough) into test cases or lighter test scenarios. Use when a tester needs to generate test coverage from any of the "five roads"…
Generates valid, boundary, and invalid test data sets for a feature by applying equivalence partitioning and boundary value analysis to a field schema or form spec. Use when a tester needs data to drive cases. Day 2 test-data block of the QA Foundational…