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Playwright Bowser

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disler
playwright-bowser

Headless browser automation using Playwright CLI. Use when you need headless browsing, parallel browser sessions, UI testing, screenshots, web scraping, or browser automation that can run in the background. Keywords - playwright, headless, browser, test, screenshot, scrape, parallel.

Overview

Publisherdisler
Repositorybowser
Skill nameplaywright-bowser
Stars
266
Forks
60
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Playwright Bowser 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/disler/bowser/tree/main/.claude/skills/playwright-bowser
  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/disler/bowser.git /tmp/bowser
mkdir -p .claude/skills
cp -r /tmp/bowser/.claude/skills/playwright-bowser .claude/skills/playwright-bowser
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Playwright Bowser 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 Bowser 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 Bowser 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 Bowser

Purpose

Automate browsers using playwright-cli — a token-efficient CLI for Playwright. Runs headless by default, supports parallel sessions via named sessions (-s=), and doesn't load tool schemas into context.

Key Details

  • Headless by default — pass --headed to open to see the browser
  • Parallel sessions — use -s=<name> to run multiple independent browser instances
  • Persistent profiles — cookies and storage state preserved between calls
  • Token-efficient — CLI-based, no accessibility trees or tool schemas in context
  • Vision mode (opt-in) — set PLAYWRIGHT_MCP_CAPS=vision to receive screenshots as image responses in context instead of just saving to disk

Sessions

Always use a named session. Derive a short, descriptive kebab-case name from the user's prompt. This gives each task a persistent browser profile (cookies, localStorage, history) that accumulates across calls.

bash
# Derive session name from prompt context:
# "test the checkout flow on mystore.com" → -s=mystore-checkout
# "scrape pricing from competitor.com"    → -s=competitor-pricing
# "UI test the login page"               → -s=login-ui-test

playwright-cli -s=mystore-checkout open https://mystore.com --persistent
playwright-cli -s=mystore-checkout snapshot
playwright-cli -s=mystore-checkout click e12

Managing sessions:

bash
playwright-cli list                                     # list all sessions
playwright-cli close-all                                # close all sessions
playwright-cli -s=<name> close                          # close specific session
playwright-cli -s=<name> delete-data                    # wipe session profile

Quick Reference

Core:       open [url], goto <url>, click <ref>, fill <ref> <text>, type <text>, snapshot, screenshot [ref], close
Navigate:   go-back, go-forward, reload
Keyboard:   press <key>, keydown <key>, keyup <key>
Mouse:      mousemove <x> <y>, mousedown, mouseup, mousewheel <dx> <dy>
Tabs:       tab-list, tab-new [url], tab-close [index], tab-select <index>
Save:       screenshot [ref], pdf, screenshot --filename=f
Storage:    state-save, state-load, cookie-*, localstorage-*, sessionstorage-*
Network:    route <pattern>, route-list, unroute, network
DevTools:   console, run-code <code>, tracing-start/stop, video-start/stop
Sessions:   -s=<name> <cmd>, list, close-all, kill-all
Config:     open --headed, open --browser=chrome, resize <w> <h>

Workflow

  1. Derive a session name from the user's prompt and open with --persistent to preserve cookies/state. Always set the viewport via env var at launch:
bash
PLAYWRIGHT_MCP_VIEWPORT_SIZE=1440x900 playwright-cli -s=<session-name> open <url> --persistent
# or headed:
PLAYWRIGHT_MCP_VIEWPORT_SIZE=1440x900 playwright-cli -s=<session-name> open <url> --persistent --headed
# or with vision (screenshots returned as image responses in context):
PLAYWRIGHT_MCP_VIEWPORT_SIZE=1440x900 PLAYWRIGHT_MCP_CAPS=vision playwright-cli -s=<session-name> open <url> --persistent
  1. Get element references via snapshot:
bash
playwright-cli snapshot
  1. Interact using refs from snapshot:
bash
playwright-cli click <ref>
playwright-cli fill <ref> "text"
playwright-cli type "text"
playwright-cli press Enter
  1. Capture results:
bash
playwright-cli screenshot
playwright-cli screenshot --filename=output.png
  1. Always close the session when done. This is not optional — close the named session after finishing your task:
bash
playwright-cli -s=<session-name> close

Configuration

If a playwright-cli.json exists in the working directory, use it automatically. If the user provides a path to a config file, use --config path/to/config.json. Otherwise, skip configuration — the env var and CLI defaults are sufficient.

json
{
  "browser": {
    "browserName": "chromium",
    "launchOptions": { "headless": true },
    "contextOptions": { "viewport": { "width": 1440, "height": 900 } }
  },
  "outputDir": "./screenshots"
}

Full Help

Run playwright-cli --help or playwright-cli --help <command> for detailed command usage.

See docs/playwright-cli.md for full documentation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Playwright Bowser AI skill do?

Headless browser automation using Playwright CLI. Use when you need headless browsing, parallel browser sessions, UI testing, screenshots, web scraping, or browser automation that can run in the background. Keywords - playwright, headless, browser, test, screenshot, scrape, parallel.

Why use Playwright Bowser on TypingMind?

Because you install it once and use it with any model. Playwright Bowser 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 Bowser in TypingMind?

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

Which AI models can use Playwright Bowser?

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 Bowser?

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

Is the Playwright Bowser AI skill free?

It is published on GitHub by disler. Check the repository for licensing terms. 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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