The Tool Desk
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What an AI agent can (and cannot) do in QA
An agent is useful at the repetitive parts of test engineering: translating acceptance criteria into test cases, exploring a page to suggest locators, generating browser steps, running a focused test, reading stack traces, proposing a repair, and producing a failure report with logs and screenshots. It can also derive boundary, negative and regression cases from requirements you state explicitly.
Those abilities do not guarantee that it will discover important defects. A generated test may pass while asserting the wrong state, use the wrong account, or miss a permission failure. A human still owns test intent, expected behavior, data design, risk decisions and merge approval.
1. Write the agent contract before it writes code
Put the rules an agent needs in the repository, rather than repeating them in every prompt. Selenium’s guidance for AI coding agents specifically warns that an agent without current references may reproduce obsolete Selenium 2 or 3 patterns. Keep the file versioned with the application.
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Include these facts
- Exact framework and browser-binding versions.
- Install, lint, type-check and test commands, including the command for one test.
- Supported browsers and viewport/device projects.
- Locator conventions, such as accessible roles, labels, stable IDs or dedicated test IDs.
- Fixture, naming, setup and teardown conventions.
- Where test accounts and data come from, and how data must be cleaned up.
- Environment URLs, required feature flags and approved credentials.
- Links to the current framework API documentation and the application’s own test guidance.
- Actions that require approval: deleting data, sending messages, changing billing, touching production or rotating secrets.
Example repository rules file
# QA agent rules
Framework: Playwright 1.x with TypeScript
Run one test: npx playwright test tests/checkout.spec.ts --project=chromium
Run headed: npx playwright test tests/checkout.spec.ts --headed
Browsers in CI: Chromium, Firefox, WebKit
Locators: prefer getByRole, getByLabel and data-testid; do not use generated classes or absolute XPath
Waits: use web-first assertions or a specific state; never add arbitrary sleeps
Data: use the seeded test account; clean up orders created by a test
Safety: never run against production; ask for approval before destructive actions
Evidence: attach trace, console output, network errors and a screenshot on failure
Tell the agent to reject an API or option that it cannot find in the versioned documentation. This simple rule prevents plausible-looking, obsolete code.
2. Give the agent a safe, observable environment
Run the application locally or in an isolated staging environment. The agent needs a real page to inspect, not only a product specification. Provide a disposable database or resettable fixtures, test-only credentials, deterministic feature flags and a network policy that blocks unapproved destinations.
Separate product failures from agent failures
For an agent that itself calls tools or models, use a deterministic harness for the agent workflow: fixed prompts, recorded tool responses and isolated sessions. The OpenAI Agents SDK documents utilities for testing agent workflows, sandbox sessions, realtime sessions and voice pipelines. Running those checks separately from browser tests helps identify whether a failure came from the application under test or from the test agent.
Capture evidence by default
- Browser trace or video for a failed test.
- Screenshot at the failure point.
- Console and network errors.
- URL, browser project, viewport and commit identifier.
- Relevant request and response data with secrets removed.
An agent can only diagnose what it receives. A bare “test failed” message encourages guessing and broad timeout changes.
3. Let the agent inspect the live application
Permit a throwaway exploration script or browser session before asking for a committed test. The agent should navigate the actual route, inspect the DOM and accessibility tree, observe the post-login state and verify which controls are present.
What to ask it to inspect
- The user journey’s entry URL and required authentication state.
- Accessible role, name and label for each control.
- Stable IDs or test IDs already used by the application.
- Loading, disabled, empty and error states.
- Whether the page changes URL, opens a dialog or updates content in place.
- Network calls that indicate completion, without coupling the test to an incidental request unless that request is the requirement.
Do not accept selectors copied from one speculative page state. If the agent cannot find a control, have it report the observed DOM and stop for clarification rather than inventing a locator.
4. Generate one focused test first
Start with one user journey and one meaningful assertion. For example: “A seeded customer can add an in-stock item to the cart, complete checkout with the test payment method and see an order confirmation.” Define the expected state precisely before generation.
Playwright example
import { test, expect } from '@playwright/test';
test('customer can complete checkout', async ({ page }) => {
await page.goto(`${process.env.BASE_URL}/login`);
await page.getByLabel('Email').fill(process.env.TEST_EMAIL!);
await page.getByLabel('Password').fill(process.env.TEST_PASSWORD!);
await page.getByRole('button', { name: 'Sign in' }).click();
await page.getByRole('link', { name: 'Catalog' }).click();
await page.getByRole('button', { name: 'Add Widget to cart' }).click();
await page.getByRole('link', { name: /cart/i }).click();
await page.getByRole('button', { name: 'Checkout' }).click();
await page.getByRole('button', { name: 'Place order' }).click();
await expect(page.getByRole('heading', { name: 'Order confirmed' })).toBeVisible();
});
This example uses role and label locators and a web-first assertion. Replace the route, labels and product name with values observed in your application. Do not copy it unchanged into a project whose UI uses different semantics.
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Prompt pattern that keeps generation bounded
Read QA-AGENTS.md. Inspect the running staging app at BASE_URL.
Implement only the “customer can complete checkout” journey.
Use the existing fixtures and locator conventions.
Add one assertion for the confirmation state.
Run the single test three times in Chromium.
If it fails, include the exception, trace and screenshot before changing code.
Do not add sleeps, weaken assertions or modify application code.
Return a unified diff and list any assumptions.5. Run, diagnose and iterate instead of hiding races
Have the agent execute the narrow test repeatedly before adding another path. Feed it the actual exception, trace, screenshot and relevant logs. Ask it to classify the failure first:
- Product defect: the application reaches an incorrect or missing state.
- Test defect: the locator, assertion, fixture or cleanup is wrong.
- Environment defect: the browser, service, seed data or network is unavailable.
- Timing defect: the test observes a transitional state.
Fix timing defects with a condition tied to the next action: a visible or enabled control, a URL change, a specific response, or a web-first assertion. Selenium’s documentation summarizes the problem precisely: “A fixed sleep is either too short, and the test fails, or too long, and the suite crawls.” Increasing every timeout can make a broken suite slower without making it reliable.
Useful diagnostic questions for the agent
- What exact state was expected, and what state was observed?
- Which locator matched zero, one or multiple elements?
- Was the element visible, enabled and attached when the action ran?
- Did a redirect, dialog, frame or new tab change the context?
- Did the test leave data or a session that affected the next run?
Require the agent to show the smallest code change that addresses the diagnosed cause. Reject a repair that merely retries the whole test, adds a long sleep or removes the assertion.
6. Review the generated diff before merging
Read the test as if it were production code. Verify that the journey matches the acceptance criterion, the assertion checks the business outcome and the account has the required permissions. Check selectors, waits, fixtures, cleanup and API versions. Ensure secrets are read from the CI secret store and are not printed in traces.
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Review checklist
- Is the test isolated from ordering and parallel workers?
- Does it create unique data or clean up what it creates?
- Are failures actionable from the attached evidence?
- Does the test avoid third-party systems that are outside the product’s control?
- Does it fail when the requirement is broken, rather than merely when text changes?
- Has a person approved any destructive or privileged action?
Selenium’s test-practices guidance makes the broader point: automation tooling alone does not create a well-architected suite. Keep ownership, conventions and review standards in the repository so future agent changes follow the same design.
Playwright or Selenium with an AI agent?
Both can work. Choose using the application’s browser, language, standards and maintenance requirements—not how quickly an agent can produce its first script.
| Decision axis | Playwright | Selenium |
|---|---|---|
| Browser coverage | One API for Chromium, Firefox and WebKit, with browser projects for matrix runs. | Cross-browser WebDriver workflows with bindings for multiple languages. |
| Locators and waits | Role, text and test-id locators are prioritized by its generator; web-first assertions encourage condition-based waiting. | Use stable locators and explicit waits; avoid fixed sleeps. Selenium recommends current bindings and Selenium Manager. |
| Debugging evidence | Traces, screenshots, video and browser-project metadata can be collected by the test setup. | Capture screenshots, logs and WebDriver evidence through the project’s test framework. |
| Standards and events | Integrated browser automation API. | WebDriver standards, with WebDriver BiDi recommended for browser events and network interception. |
| Agent documentation | Point the agent to the current Playwright version and locator guidance. | Point the agent to the current Selenium binding, WebDriver, Selenium Manager and BiDi references. |
| Parallel CI | Use projects and workers after the focused test is repeatable. | Use isolated sessions, a grid or equivalent infrastructure after the focused test is repeatable. |
Whichever framework you choose, keep the agent’s contract explicit and reject APIs that are not present in the version you run.
Scaling from one test to a dependable suite
Add coverage by risk
After the first flow passes repeatedly, add the highest-risk journeys: authentication and authorization boundaries, payments or other irreversible actions, critical forms, error recovery and data-import paths. Ask the agent to derive boundary and negative cases from written acceptance criteria, then review each expected result.
Expand the browser matrix deliberately
Add Chromium, Firefox and WebKit projects in Playwright, or the browsers required by your users in Selenium. Keep the same test intent while allowing browser-specific setup only where the behavior genuinely differs. A failing browser project should include its own screenshot, trace and environment details.
Run in CI with controlled parallelism
Parallel workers reduce elapsed time only when fixtures, accounts and services are isolated. Start with a small worker count, measure queue and startup costs, and increase it after confirming that tests do not share mutable state. Cache dependencies where your CI permits it, but do not cache sessions or generated data that should be fresh.
Track maintenance signals
Review flaky-test frequency, rerun outcomes, time to diagnose and the proportion of failures classified as product, test or environment defects. These are operational signals, not universal productivity percentages; there is no broadly applicable defect-detection or maintenance percentage that can be promised for AI-generated tests.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Failure modes and precise fixes
The agent uses an obsolete method
Cause: the prompt or repository points to an old example. Fix: pin the framework version, link the current API reference and require the agent to verify every method against it.
Selectors break after harmless UI changes
Cause: generated class names, positional selectors or absolute XPath. Fix: use accessible roles and labels, stable IDs or dedicated test IDs; ask the agent to report when none is available.
The test fails intermittently at navigation
Cause: the next action races a redirect, rendering step or API response. Fix: wait for the specific URL, state or web-first assertion that represents readiness. Do not add a blanket sleep.
Everything passes but the bug remains
Cause: the assertion checks a cosmetic detail or the wrong account state. Fix: restate the business outcome, verify permissions and data, and require an assertion on the resulting state or persisted record.
Parallel runs contaminate one another
Cause: shared accounts, fixed identifiers or incomplete teardown. Fix: allocate worker-safe data, isolate sessions and clean up records in a finally-style fixture.
The agent attempts a dangerous action
Cause: broad credentials or an underspecified task. Fix: use staging-only accounts, block production destinations, require approval gates and make destructive operations explicit in the contract.
Or skip the browser setup
When you need a screenshot for a test artifact, bug report or visual checkpoint, ScreenshotNeo can capture the page through one request instead of maintaining a browser script. It accepts the consent banner like a visitor, then removes more than 60 known consent platforms, newsletter popups and chat widgets before the capture; each cleanup step can be turned off. Only clean shots are billed. Bot checks or CAPTCHAs, blank pages, timeouts, failed loads and cache hits cost nothing, and the response identifies the result with X-Page-Verdict and X-Billed headers.
cURL (see the ScreenshotNeo documentation):
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://your-staging.example.com -o shot.webpPython:
import requests
r = requests.get("https://api.screenshotneo.com/v1/shot", params={"access_key": "YOUR_API_KEY", "url": "https://your-staging.example.com"}, timeout=90)
open("shot.webp", "wb").write(r.content)Node.js:
const q = new URLSearchParams({ access_key: 'YOUR_API_KEY', url: 'https://your-staging.example.com' });
const res = await fetch(`https://api.screenshotneo.com/v1/shot?${q}`);For QA evidence, its options include full-page capture with lazy images loaded, a CSS-selected element, dark mode, 12 device presets or any viewport, retina scale, custom CSS and JavaScript, clicks before capture, selector hiding, waits for a selector, delay or network idle, blocking ads, trackers, requests or resource types, custom headers, cookies, user agent and Authorization, timezone and geolocation, transparent backgrounds, resizing, chosen-TTL caching, signed links for public image tags, asynchronous jobs with signed webhooks, bulk capture of up to 100 URLs per call, a usage API and an OpenAPI specification. It also supports PDF output with paper size, margins, landscape and page ranges, HTML/CSS-to-image capture, and an MCP server with take_screenshot, get_page_info and capture_pdf tools for Claude, Cursor and other MCP clients.
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- Version the agent contract with framework versions, commands, locators, matrix and safety boundaries.
- Run the application in isolated staging with resettable data and approved credentials.
- Let the agent inspect the live DOM and accessibility tree.
- Generate one focused journey with one business-level assertion.
- Run it repeatedly and provide real traces, screenshots, logs and exceptions.
- Fix causes with resilient locators and condition-based waits, never blanket sleeps.
- Review intent, permissions, data isolation, cleanup and the complete diff.
- Expand by risk, then add browser projects and CI parallelism.
Frequently Asked Questions
How many tests should an agent generate in one request?
Start with one user journey and one expected outcome. Small diffs make locator, data and assertion errors easy to review; ask for additional cases only after that flow is repeatable.
How should tests handle an external payment or email provider?
Keep the browser test focused on your product and use a sandbox, stub or contract fixture for the provider. Record the dependency and test the integration separately so an outage is not misclassified as a product regression.
What should happen to generated tests that are not ready to merge?
Keep them in the agent’s branch or draft change, with the observed assumptions and evidence attached. Do not silently commit speculative selectors or disabled assertions.
The Bottom Line
AI agents make QA faster when they operate inside a written contract, inspect the real application, use resilient locators and condition-based waits, and produce evidence that a person can review. Treat every generated test as a proposed change, prove one focused flow first, then scale coverage and browsers deliberately.
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