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vasilyu1983/ai-agents-public656 installs

qa-testing-playwright

Builds and debugs Playwright E2E suites. Use when authoring browser tests, fixing flakes, or hardening Playwright CI and locator strategy.

How do I install this agent skill?

npx skills add https://github.com/vasilyu1983/ai-agents-public --skill qa-testing-playwright
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill provides a comprehensive and secure set of instructions, references, and templates for performing E2E testing with Playwright. It emphasizes best practices such as semantic locators, test isolation, and artifact-based debugging while providing secure patterns for authentication and CI/CD integration. No malicious patterns or security risks were identified.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • Runlayerfail

    7/12 files flagged

What does this agent skill do?

QA Testing (Playwright)

Core docs:

Quick Reference

NeedGo to
Run the Playwright workflow## Workflow
Apply defaults and authoring rules## Defaults and ## Authoring Rules
Debug flaky or blocked runs## Debugging Checklist and ## Execution Preflight
Decide tool fit, selectors, flake triage order, sharding cost## Expert Judgment
Load templates and references## Resources and ## Templates

Defaults

  • Keep E2E thin: protect critical user journeys only; push coverage down (unit/integration/contract).
  • Locator priority: getByRole → getByLabel/getByText → getByTestId (fallback).
  • Waiting: rely on Playwright auto-wait + web-first assertions; no sleeps/time-based waits.
  • Isolation: tests must run alone, in parallel, and in any order; eliminate shared mutable state. When a shared resource cannot be isolated (external service, global account setting), declare a named test lock (1.63+: test(title, { lock: 'user-settings' }, fn)) instead of workers: 1 or describe.serial for the whole file.
  • Local execution posture: choose one server topology first (shared dev stack or Playwright-managed webServer), then triage with an exact spec or named batch plus --workers=1.
  • Flake posture: retries are a debugging tool; treat rerun-pass as a failure signal and fix root cause.
  • CI flakes: prefer built-in failOnFlakyTests (1.52+); the custom reporter template is legacy, for pre-1.52 pins only.
  • CI posture: smoke gate on PRs; shard/parallelize regression on schedule; always keep artifacts (trace/video/screenshot).
  • Oracle posture: assert the user outcome; do not wait on incidental network requests when the visible result can be verified directly.
  • AI posture: use Playwright codegen / test agents / MCP for scaffolding and exploration, then harden assertions and fixtures manually.
  • Component tests: use the built-in stories/gallery mount('components/X/Story') fixture from @playwright/test (1.62+). The @playwright/experimental-ct-* packages were frozen in 1.63 and the docs now say they are removed; stay on 1.62 until migrated. See references/playwright-patterns.md#component-testing.
  • Visual regression: native toHaveScreenshot when one OS/browser baseline set in Docker is enough; a hosted service when designers review diffs or the browser/OS matrix makes committed baselines unmanageable. See references/visual-regression-testing.md.
  • Browser MCP: Playwright MCP for test generation + accessibility; Chrome DevTools MCP for performance / network / console debugging. See references/playwright-mcp.md.
  • CLI posture: for high-throughput coding agents, prefer the Playwright CLI (npx playwright cli; shell commands) over Playwright MCP — it avoids the MCP protocol's per-call token overhead. Check npx playwright cli --version / release notes for your installed version before relying on it, since CLI availability and flags vary by release. The official docs call it token-efficient without a number; treat any specific token-count figure (e.g. a "tokens/task" comparison) as a claim to verify against your own measurement, not a quotable fact. Use MCP (npx playwright mcp) when persistent browser state and rich introspection are needed.
  • Local iteration posture: use npx playwright test --only-changed=main to run only tests affected by uncommitted/branch changes during authoring; it is a heuristic over the import graph, so always run the full suite (or the deploy-gate replay) before merging — never treat --only-changed green as release-ready signal.

Quick Start

CommandPurpose
npm init playwright@latestInitialize Playwright
npx playwright testRun all tests
npx playwright test --grep @smokeRun smoke tests
npx playwright test --project=chromiumRun a single project
npx playwright test --uiDebug with UI mode
npx playwright test --debugStep through a test
npx playwright codegenRecord a flow and bootstrap a test
npx playwright init-agents --loop=claudeInitialize test agents for Claude Code (--loop=codex, vscode, opencode also exist)
npx playwright test --debug=cliLet a coding agent attach and debug a test via playwright-cli (1.59+)
npx playwright test --last-failedRerun only the tests that failed in the last run
npx playwright test --fail-on-flaky-testsFail CI if any test is flaky
npx playwright show-trace trace.zipInspect trace artifacts
npx playwright show-reportInspect HTML report
npx playwright trace open <trace.zip>Open a trace for CLI analysis; then trace actions, trace action <n>, trace snapshot <n> --name after, trace close (1.59+)
npx playwright test --only-changed=mainRun only tests affected by changes since main (heuristic — always follow with a full run before release)

Local Execution Topology

Use this order by default:

  1. Start one shared local dev stack if the repo already provides it; prefer reusing it with --no-server over spawning a fresh app per rerun.
  2. Prove which build handles the request: record source revision or build ID, base URL, server process/start command, environment, and service-worker or CDN cache state. A listening port can serve stale code; if identity is unavailable, label the result runtime observed, build identity unverified.
  3. Reproduce with one exact spec or one named batch and --workers=1.
  4. Fix and rerun the smallest affected scope.
  5. Run the deploy-gate replay only after the targeted scope is green.

Default suite tiers:

  • Smoke: PR gate and fastest signal.
  • Targeted batch/spec: local triage and deflake work.
  • Deploy-gate replay: dependency-chain or critical-journey replay for release confidence.

Avoid local full-suite reruns as the first move unless the job is explicitly “prove deploy readiness now.”

When to Use

  • E2E tests for web applications
  • Test user authentication flows
  • Verify form submissions
  • Test responsive designs
  • Automate browser interactions
  • Set up Playwright in CI/CD

When NOT to Use

ScenarioUse Instead
Unit testingJest, Vitest, pytest
API contractsqa-api-testing-contracts
Load testingk6, Locust, Artillery
Mobile nativeAppium
Pure business-logic or data-transform correctnessUnit tests — a browser adds latency and flake with zero extra confidence
Cross-team API contract driftConsumer-driven contract tests, not a UI click-path proxy
Component-level visual/interaction isolation at scalePlaywright stories/gallery component tests (1.62+, stable) if you already run Playwright; Storybook + Chromatic/Percy if the team reviews visual diffs in a hosted UI (see Defaults)
Thousands of input-combination fuzzingProperty-based testing at the unit layer; E2E cannot afford the runtime

Expert Judgment

When Playwright Is the Wrong Tool

Playwright (or any browser E2E tool) is the wrong choice when a faster, cheaper layer already proves the same risk:

  • If the bug class can be caught by a type system, unit test, or schema/contract check, push it down — E2E is the most expensive test layer per assertion (browser boot, network, rendering).
  • If the "user journey" is actually an internal API call with no meaningful UI branching, test the API directly (request fixture or a dedicated API-testing skill) and skip the browser.
  • If you are testing a third-party surface you do not control (payment provider hosted page, OAuth consent screen), do not chase it with E2E; mock the boundary and test your own integration contract instead — third-party UI changes make these tests flaky by design, not by mistake.
  • If the same risk is already covered by a component test or visual snapshot at a fraction of the cost, do not duplicate it in E2E "just to be safe" — duplicate coverage without duplicate risk is waste, not thoroughness.

Selector-Strategy Decision Rule

Pick the locator in this order, and stop at the first one that resolves unambiguously to exactly one element:

  1. getByRole with an accessible name — this is what a screen reader and a real user both key off, so it survives markup refactors.
  2. getByLabel / getByText — use when there is no meaningful role (plain text, decorative containers) but the visible copy is stable.
  3. getByTestId — use only when the element has no stable role/label (e.g., a canvas, a drag handle, a duplicate-name list item) or when semantic locators would force asserting on implementation detail (raw CSS class, generated ID). Never fall back to raw CSS or XPath as a first resort — they are a signal that the markup itself may need an accessibility fix, not just a test workaround.

Flakiness Triage Order (Fastest Signal First)

Before touching a single assertion, classify the failure in this order — each step is strictly cheaper than the next, so do not skip ahead:

  1. Selector ambiguity — trace shows the locator resolved to 0 or 2+ elements. Fix the locator, not the wait.
  2. Missing wait / race — trace shows the action fired before the element was actionable. Replace with a web-first assertion; never add a fixed sleep.
  3. State leakage — failure only reproduces after other tests ran (parallel workers, shared fixtures, undropped test data). Fix isolation before touching this test's own code. If the shared resource cannot be isolated, put a named lock on exactly the tests that touch it (1.63+) rather than serializing the suite.
  4. Environment — only fails in CI, not locally; look at concurrency, cold start, CPU starvation, and container resource limits before assuming a product bug.
  5. Stateful-app classes — for auth-heavy or backend-driven apps, also classify auth-state, state-sync, optional-network, and degraded-mode (see ### Stateful App Failure Classes) before assuming a product bug.
  6. Product regression — only after 1-5 are ruled out with trace evidence, treat the failure as reflecting the app under test and file/fix accordingly. Retries mask all of these; use retries to gather evidence (trace/video) on the first CI run, but treat "passed on retry" as an unresolved defect, not a pass (failOnFlakyTests: true).

Flake forensics tooling (check availability against your pinned version):

  • retryStrategy: 'isolated' (1.62+) runs all retries at the end, one by one in a single worker. A test that fails in-suite but passes isolated points to interference (step 3); one that still fails isolated points to steps 1, 2 or 6.
  • trace: 'retain-on-failure-and-retries' (1.59+; a video mode since 1.61) keeps both the failing and the passing attempt, so you can diff them side by side.
  • --repeat-each=N on the single suspect test proves a fix; --last-failed reruns only the previous failures.
  • Quarantine: tag @flaky with an owner and an exit date, and exclude it from the gate with --grep-invert @flaky or a Reporter.preprocess() skip list (1.62+). A quarantined test with no owner is a deleted test.

CI Parallelism Economics (Worked Example)

Sharding trades machine-cost for wall-clock time; the math to decide is straightforward. Given a suite that takes T minutes single-threaded and N shards each with M machine-minutes of fixed overhead (checkout, install, browser download):

  • Wall-clock per shard ≈ T/N + M.
  • Total machine-minutes billed ≈ N × (T/N + M) = T + N×M.

Example: T = 60 min, M = 3 min fixed overhead per shard/job.

  • 1 shard: wall-clock = 63 min, billed = 63 machine-minutes.
  • 4 shards: wall-clock = 60/4 + 3 = 18 min, billed = 4 × 18 = 72 machine-minutes.
  • 12 shards: wall-clock = 60/12 + 3 = 8 min, billed = 12 × 8 = 96 machine-minutes.

Sharding always costs more total machine-minutes (because fixed overhead is paid N times) — the return is faster PR feedback, not lower spend. The judgment call: shard the PR-gate smoke suite (wall-clock matters, suite is small so N×M stays small) and run the full regression unsharded or lightly sharded on a schedule (spend matters more than latency there). Re-derive this ratio with your own T and M before picking a shard count — do not copy N=4 by convention.

Authoring Rules

Locator Strategy

// 1. Role locators (preferred)
await page.getByRole('button', { name: 'Sign in' }).click();

// 2. Label/text locators
await page.getByLabel('Email').fill('user@example.com');

// 3. Test IDs (fallback)
await page.getByTestId('user-avatar').click();

Flake Control

  • Avoid sleeps; use Playwright auto-wait
  • Use retries as signal, not a crutch
  • Prefer built-in failOnFlakyTests in CI
  • Capture trace/screenshot/video on failure
  • Prefer user-like interactions; avoid force: true

Workflow

  • Write the smallest test that proves the user outcome (intent + oracle).
  • Make execution topology explicit before triage: shared dev stack vs Playwright webServer, plus exact start/stop commands.
  • Reproduce with one exact spec or named batch before expanding scope.
  • Stabilize locators and assertions before adding more steps.
  • Make state explicit: seed per test/worker, clean up deterministically, and verify auth/subscription/test-data reset paths for stateful apps.
  • Mock or isolate third-party boundaries where they are not part of the user-facing oracle.
  • In CI: shard/parallelize, capture artifacts, and fail fast on rerun-pass flakes.

Debugging Checklist

If something is flaky:

  • Open trace and error artifacts first; identify whether the failure is selector ambiguity, missing wait, state leakage, or the wrong server topology.
  • If the trace lands on login or an unexpected redirect, classify auth-state before changing assertions.
  • If browser logs show 429 or Retry-After on side endpoints, decide whether that request is part of the oracle or only noise.
  • Replace brittle selectors with semantic locators; replace sleeps with expect(...), an auth-aware navigation helper, or a targeted readiness assertion.
  • Remove waits on incidental requests; assert the visible route, action, or content outcome instead.
  • Reduce global timeouts; add scoped timeouts only when the product truly needs it — prefer a per-action timeout or test.step(name, fn, { timeout }) over raising timeout in playwright.config.ts.
  • If it only fails in CI, look for concurrency, cold-start, CPU starvation, and environment differences.

Execution Preflight

Before expensive E2E runs, run the preflight in references/playwright-preflight-sandbox.md (spec paths, port/host binding, one server topology, build locks, per-test timeout budget, EPERM/EACCES escalation) and record the answers with assets/template-playwright-preflight-checklist.md. Treat EADDRINUSE, missing spec/result paths and shell-glob failures on bracketed route segments as environment failures, not product bugs.

Stateful App Failure Classes

  • auth-state: protected route unexpectedly redirects to login or loses storage/session state.
  • state-sync: backend reset or webhook succeeded, but UI has not converged yet.
  • optional-network: a side request failed, but the user-visible oracle may still be correct.
  • degraded-mode: rate limits or fallback UX activated and should be asserted intentionally.

Resources

ResourcePurpose
references/playwright-mcp.mdMCP & AI testing
references/playwright-patterns.mdAdvanced patterns
references/playwright-ci.mdCI configurations
references/playwright-authentication.mdAuth patterns and session management
references/visual-regression-testing.mdVisual regression (library canonical): native vs hosted, baselines, thresholds
references/api-testing-playwright.mdrequest fixture for UI+API hybrid tests (contract/schema work lives in qa-api-testing-contracts)
references/playwright-preflight-sandbox.mdSandbox/port preflight and escalation decisions
data/sources.jsonDocumentation links

Templates

TemplatePurpose
assets/template-playwright-e2e-review-checklist.mdE2E review checklist
assets/template-playwright-fail-on-flaky-reporter.jsLegacy: fail CI on rerun-pass flakes for Playwright < 1.52 only; use failOnFlakyTests otherwise
assets/test-fail-on-flaky-reporter.test.jsnode --test checks for the legacy flaky reporter
assets/template-playwright-preflight-checklist.mdPreflight checklist for port/sandbox/timeouts

Navigation

Use Quick Reference to select the workflow, debugging path, or resource.

Related Skills

SkillPurpose
qa-testing-strategyOverall test strategy
software-frontendFrontend development
ops-devops-platformCI/CD integration

Verification Gate

Before delivering, check:

  • If a Playwright project exists, provide the exact test command to run and execute it when the environment is available; otherwise mark execution as unverified.
  • Generated selectors follow the stated locator priority unless the page makes that impossible.
  • The output avoids sleep-based waits and names the readiness assertion or trace/debug artifact to inspect.
  • Every referenced test file, config file, and command path exists in the repo or is explicitly marked as proposed.

Learnings Loop

When prior decisions or pitfalls are relevant, consult learnings.consolidated.md if present; use learnings.md only for needed history or as the available fallback. Otherwise skip both.

After applying it, if you encountered a pattern worth remembering, a mistake worth preventing, or a domain fact that surprised you, append one dated bullet to learnings.md via agents-skills-feedback-loop/scripts/append_learning.py. Do not modify SKILL.md itself.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/vasilyu1983/ai-agents-public/qa-testing-playwright">View qa-testing-playwright on skillZs</a>