> For the complete documentation index, see [llms.txt](https://docs.currents.dev/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.currents.dev/ai/agent-skills/agent-skill-playwright-best-practices.md).

# Playwright best practices

An agent skill that teaches AI agents to write, debug and maintain Playwright tests the way an experienced Playwright engineer would

Without guidance, agents write Playwright tests from generic patterns: `waitForTimeout` calls, brittle CSS selectors, and retries that hide real bugs. This [agent skill](https://agentskills.io/home) gives them Playwright practice instead: locators, web-first assertions, debugging flaky tests, CI setup and more.

```bash
npx skills add https://github.com/currents-dev/playwright-best-practices-skill
```

The source is [on GitHub](https://github.com/currents-dev/playwright-best-practices-skill). It works in Claude Code, Cursor, VS Code, Gemini CLI and other agents that read skills. The agent loads it when a task involves Playwright; you do not need to name it.

## What it covers

| Area                | Examples                                                                          |
| ------------------- | --------------------------------------------------------------------------------- |
| Writing tests       | E2E, component, API, visual regression and accessibility tests                    |
| Fixing tests        | Flaky tests, timeouts in CI, debugging failures                                   |
| Browser features    | File uploads, OAuth popups, multi-tab flows, iframes, service workers, WebSockets |
| Devices and locales | Mobile layouts, touch gestures, geolocation, i18n and RTL                         |
| Test structure      | Page Object Model, fixtures, global setup and teardown                            |
| CI and scale        | Projects, dependencies, parallel runs and sharding                                |
| Other apps          | Electron apps and browser extensions                                              |

Example prompts:

* "Fix this flaky login test."
* "Add a test for the checkout flow."
* "Mock the payment gateway in tests."
* "Set up sharding for our test suite in CI."


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.currents.dev/ai/agent-skills/agent-skill-playwright-best-practices.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.