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Playwright Triage

OrganizationPopular
microsoft
playwright-triage

Triage a Playwright bug report by reproducing it from the information in the issue. Use when asked to triage, reproduce, or verify a GitHub issue (a new bug report, or an existing report with a new comment).

Overview

Publishermicrosoft
Repositoryplaywright
Skill nameplaywright-triage
Stars
96.9K
Forks
6.5K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Playwright Triage AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/microsoft/playwright/tree/main/.claude/skills/playwright-triage
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/playwright.git /tmp/playwright
mkdir -p .claude/skills
cp -r /tmp/playwright/.claude/skills/playwright-triage .claude/skills/playwright-triage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Playwright Triage in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Playwright Triage on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Playwright Triage is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Playwright Issue Triage

Triage a GitHub issue by working out what it actually is, then doing the right thing for that kind. The goal is a clear, verified status, not a fix.

First, classify the issue

Judge by the content, not the label — a "[Feature]" is often really a bug (something already should work), and a "[Bug]" is sometimes expected behaviour. Work out what it actually is:

  • Bug — reproduce it. The bulk of this skill.
  • Feature request — nothing to reproduce. Check it doesn't already exist (search docs/API, maybe under another name), verify any source the reporter cites by reading it, and surface the real design question. If it's small and well-scoped (like "fail loudly instead of silently"), the ideal takeaway is an acceptance test: one self-contained spec asserting current behaviour (passes today) with the desired behaviour alongside as a fixme/commented assertion.
  • Upstream / environment — a genuinely external owner (the Node project, a browser engine, a website's own server/cert config), not Playwright. Find the real owner, don't brute-force a repro, verify any cited upstream issue and point at the real fix path. Note: the Playwright family — @playwright/mcp (source lives here under packages/playwright-core/src/tools/mcp/), playwright-vscode, -python, -java, -dotnet — is not "upstream"; it's us. Never tell a reporter to refile within the project (see below).
  • Question / usage — answer it or point at the docs.

The rest of this skill is the bug path.

Reproducing a bug

You're not in a hurry, so be exhaustive before giving up. If the user has provided a minimal repro, try it first. If it does not repro for you, play around with things they might have forgotten to mention: all three browsers, headed/headless, a few recent versions, and variations of the snippet or trigger. Report "cannot reproduce" only after you've genuinely explored — and say what you tried. If you have a hunch for what information would help, ask for it.

Run across browsers, and watch for divergence — a bug that only reproduces in webkit, or everywhere except firefox, is a strong signal worth leading with. Plenty of bugs are browser-agnostic, though, and those are just as real: reproducing on every browser is a good result to report, not a non-finding.

  1. Read the whole thread, comments included — the missing repro or narrowed trigger is often there.
  2. Pull the inputs: version, browser(s), OS, repro repo/snippet, Expected-vs-Actual (your oracle). If something's missing, guess and try anyway; note assumptions in the report.
  3. Reproduce on tip-of-tree first, in ~/tmp/issue-<number>/: clone the linked repo, or scaffold npm install @playwright/test@next with a single-project config (see bisect-published-versions.md). Use PLAYWRIGHT_HTML_OPEN=never. If it reproduces on ToT, it's a live bug — record the exact version/sha you tested, and if it looks like a regression, bisect it (see the guide).
  4. If ToT doesn't reproduce it, try the version the user reported. If it reproduces there but not on ToT, it's already fixed — find the version/PR that fixed it (a cherry-pick may still be worth it). If neither reproduces, it's incomplete or env-specific — say what you couldn't match. (A version ending in -next, e.g. 1.62.0-next, is not an npm version — it means tip-of-tree, which is the @next build you already tried.)
  5. If ToT does reproduce it - search for related reports. Check the issue timeline for cross-references first. Use GitHub MCP issue and pull request search tools, not gh in CI, and limit this to a handful of searches. Search open and closed issues and PRs with queries such as repo:microsoft/playwright "exact error string" and repo:microsoft/playwright <API name> <trigger>. Also search the relevant family repos: microsoft/playwright-python, microsoft/playwright-java, microsoft/playwright-dotnet, and microsoft/playwright-vscode. Read useful matches and linked changes, including maintainer decisions and follow-up reports. Compare the API usage, trigger, versions, and behavior, not just titles. Check whether an existing API or option actually meets the reporter's goal rather than avoiding the failing operation. If the existing evidence establishes a duplicate or a shipped fix for the reporter's conditions, report that status without repeating the reproduction.

To step through a test interactively, use the playwright-cli skill.

Reports sometimes target another part of the Playwright project — @playwright/mcp (its source is in this repo), playwright-vscode, playwright-python, playwright-java, playwright-dotnet. These are all us, so triage them like anything else: check out that repo and reproduce there in its own language/toolchain when needed. Never tell the reporter the issue belongs in a different Playwright repo or should be refiled there — that's an internal routing detail, not the reporter's problem.

Condense the repro into a self-contained test

Big or app-specific repros are much more useful boiled down to a single self-contained spec, written the way our tests are: one test(...) using the page and server fixtures, tagged with the issue link. Crucially:

  • No test.beforeAll / afterAll, no http.createServer, no manual setup/teardown. The fixtures already give you a page and a web server. Use server.setRoute(...), server.setRedirect(...), server.PREFIX, server.EMPTY_PAGE instead of standing up your own.
  • Drive the page with page.setContent(...) or page.goto(server.PREFIX + '/...').
  • Keep only what's needed to trigger the bug, and end on the assertion that fails.

Drop it into the repo (tests/page/) and run it with npm run ctest.

Mirror real self-contained tests, e.g.:

Verify related fixes

For a related PR, check whether it is open, closed without merging, or merged, and whether the fix has shipped and in which version. Run the condensed repro against the PR branch when available, recording the exact commit and result. If the fix has shipped, verify the repro on that release too. Report anything you could not verify rather than treating an open or merged PR as proof of a fix.

Report

Give a status that fits the issue type — for a bug: reproduced / fixed-on-latest / cannot-reproduce / not-a-bug / duplicate of #N; for a feature request or upstream/env issue: a short verdict (already-possible, valid request, upstream — owned by X) — plus the evidence. For bugs, include the condensed repro and be exhaustive about what you ran — the full matrix of browsers, versions, and variations you tried, not just the one that worked — so the reader can trust the verdict and skip re-checking. Call out any browser-specific divergence. Write it in the Playwright bot voice (.github/workflows/bot-voice.md, relative to the repo root) — maintainer voice, not AI-speak.

Watch out

  • Only run code you trust — skim a linked repo/snippet first; bail and report that in the issue comment if it has postinstall scripts, obfuscated code, or random small libraries.
  • Triage ends at a reproduction and a status; don't jump to a fix.

Frequently asked questions

What does the Playwright Triage AI skill do?

Triage a Playwright bug report by reproducing it from the information in the issue. Use when asked to triage, reproduce, or verify a GitHub issue (a new bug report, or an existing report with a new comment).

Why use Playwright Triage on TypingMind?

Because you install it once and use it with any model. Playwright Triage is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Playwright Triage in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/playwright/tree/main/.claude/skills/playwright-triage. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Playwright Triage?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Playwright Triage?

As many as you like. As long as a model supports skills, you can use Playwright Triage with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Playwright Triage AI skill free?

Yes. It is published on GitHub by microsoft under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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