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Playwright Ci Caching

CommunityPopular
Aaronontheweb
playwright-ci-caching

Cache Playwright browser binaries in CI/CD pipelines (GitHub Actions, Azure DevOps) to avoid 1-2 minute download overhead on every build.

Overview

PublisherAaronontheweb
Repositorydotnet-skills
Skill nameplaywright-ci-caching
Stars
1.2K
Forks
110
Bundled files
Instructions only
LicenseMIT
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 Aaronontheweb on GitHub. Read the source before you install it.

Installation

Install the Playwright Ci Caching 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/Aaronontheweb/dotnet-skills/tree/master/skills/playwright-ci-caching
  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/Aaronontheweb/dotnet-skills.git /tmp/dotnet-skills
mkdir -p .claude/skills
cp -r /tmp/dotnet-skills/skills/playwright-ci-caching .claude/skills/playwright-ci-caching
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Playwright Ci Caching 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 Ci Caching 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 Ci Caching 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.

Caching Playwright Browsers in CI/CD

When to Use This Skill

Use this skill when:

  • Setting up CI/CD for a project with Playwright E2E tests
  • Build times are slow due to browser downloads (~400MB, 1-2 minutes)
  • You want automatic cache invalidation when Playwright version changes
  • Using GitHub Actions or Azure DevOps pipelines

The Problem

Playwright browsers (~400MB) must be downloaded on every CI run by default. This:

  • Adds 1-2 minutes to every build
  • Wastes bandwidth
  • Can fail on transient network issues
  • Slows down PR feedback loops

Core Pattern

  1. Extract Playwright version from Directory.Packages.props (CPM) to use as cache key
  2. Cache browser binaries using platform-appropriate paths
  3. Conditional install - only download on cache miss
  4. Automatic cache bust - key includes version, so package upgrades invalidate cache

Cache Paths by OS

OSPath
Linux~/.cache/ms-playwright
macOS~/Library/Caches/ms-playwright
Windows%USERPROFILE%\AppData\Local\ms-playwright

GitHub Actions

yaml
- name: Get Playwright Version
  shell: pwsh
  run: |
    $propsPath = "Directory.Packages.props"
    [xml]$props = Get-Content $propsPath
    $version = $props.Project.ItemGroup.PackageVersion |
      Where-Object { $_.Include -eq "Microsoft.Playwright" } |
      Select-Object -ExpandProperty Version
    echo "PlaywrightVersion=$version" >> $env:GITHUB_ENV

- name: Cache Playwright Browsers
  id: playwright-cache
  uses: actions/cache@v4
  with:
    path: ~/.cache/ms-playwright
    key: ${{ runner.os }}-playwright-${{ env.PlaywrightVersion }}

- name: Install Playwright Browsers
  if: steps.playwright-cache.outputs.cache-hit != 'true'
  shell: pwsh
  run: ./build/playwright.ps1 install --with-deps

Multi-OS GitHub Actions

For workflows that run on multiple operating systems:

yaml
- name: Cache Playwright Browsers
  id: playwright-cache
  uses: actions/cache@v4
  with:
    path: |
      ~/.cache/ms-playwright
      ~/Library/Caches/ms-playwright
      ~/AppData/Local/ms-playwright
    key: ${{ runner.os }}-playwright-${{ env.PlaywrightVersion }}

Azure DevOps

yaml
- task: PowerShell@2
  displayName: 'Get Playwright Version'
  inputs:
    targetType: 'inline'
    script: |
      [xml]$props = Get-Content "Directory.Packages.props"
      $version = $props.Project.ItemGroup.PackageVersion |
        Where-Object { $_.Include -eq "Microsoft.Playwright" } |
        Select-Object -ExpandProperty Version
      Write-Host "##vso[task.setvariable variable=PlaywrightVersion]$version"

- task: Cache@2
  displayName: 'Cache Playwright Browsers'
  inputs:
    key: 'playwright | "$(Agent.OS)" | $(PlaywrightVersion)'
    path: '$(HOME)/.cache/ms-playwright'
    cacheHitVar: 'PlaywrightCacheHit'

- task: PowerShell@2
  displayName: 'Install Playwright Browsers'
  condition: ne(variables['PlaywrightCacheHit'], 'true')
  inputs:
    filePath: 'build/playwright.ps1'
    arguments: 'install --with-deps'

Helper Script: playwright.ps1

Create a build/playwright.ps1 script that discovers and runs the Playwright CLI. This abstracts away the Playwright CLI location which varies by project structure.

powershell
# build/playwright.ps1
# Discovers Microsoft.Playwright.dll and runs the bundled Playwright CLI

param(
    [Parameter(ValueFromRemainingArguments = $true)]
    [string[]]$Arguments
)

# Find the Playwright DLL (after dotnet build/restore)
$playwrightDll = Get-ChildItem -Path . -Recurse -Filter "Microsoft.Playwright.dll" -ErrorAction SilentlyContinue |
    Select-Object -First 1

if (-not $playwrightDll) {
    Write-Error "Microsoft.Playwright.dll not found. Run 'dotnet build' first."
    exit 1
}

$playwrightDir = $playwrightDll.DirectoryName

# Find the playwright CLI (path varies by OS and node version)
$playwrightCmd = Get-ChildItem -Path "$playwrightDir/.playwright/node" -Recurse -Filter "playwright.cmd" -ErrorAction SilentlyContinue |
    Select-Object -First 1

if (-not $playwrightCmd) {
    # Try Unix executable
    $playwrightCmd = Get-ChildItem -Path "$playwrightDir/.playwright/node" -Recurse -Filter "playwright" -ErrorAction SilentlyContinue |
        Where-Object { $_.Name -eq "playwright" } |
        Select-Object -First 1
}

if (-not $playwrightCmd) {
    Write-Error "Playwright CLI not found in $playwrightDir/.playwright/node"
    exit 1
}

Write-Host "Using Playwright CLI: $($playwrightCmd.FullName)"
& $playwrightCmd.FullName @Arguments

Usage:

bash
# Install browsers
./build/playwright.ps1 install --with-deps

# Install specific browser
./build/playwright.ps1 install chromium

# Show installed browsers
./build/playwright.ps1 install --dry-run

Prerequisites

This pattern assumes:

  1. Central Package Management (CPM) with Directory.Packages.props:

    xml
    <Project>
      <ItemGroup>
        <PackageVersion Include="Microsoft.Playwright" Version="1.40.0" />
      </ItemGroup>
    </Project>
  2. Project has been built before running playwright.ps1 (so DLLs exist)

  3. PowerShell available on CI agents (pre-installed on GitHub Actions and Azure DevOps)

Why Version-Based Cache Keys Matter

Using the Playwright version in the cache key ensures:

  • Automatic invalidation when you upgrade Playwright
  • No stale browser binaries that don't match the SDK version
  • No manual cache clearing needed after version bumps

If you hardcode the cache key (e.g., playwright-browsers-v1), you'll need to manually bump it every time you upgrade Playwright, or you'll get cryptic version mismatch errors.

Troubleshooting

Cache not being used

  1. Verify the version extraction step outputs the correct version
  2. Check that the cache path matches your OS
  3. Ensure Directory.Packages.props exists and has the Playwright package

"Browser not found" after cache hit

The cached browsers don't match the Playwright SDK version. This happens when:

  • The cache key doesn't include the version
  • The version extraction failed silently

Fix: Ensure the Playwright version is in the cache key.

playwright.ps1 can't find the DLL

Run dotnet build or dotnet restore before running the script. The Playwright DLL only exists after NuGet restore.

References

This pattern is battle-tested in production projects:

Related Skills

  • dotnet-skills:playwright-blazor - Writing Playwright tests for Blazor applications
  • dotnet-skills:project-structure - Central Package Management setup

Frequently asked questions

What does the Playwright Ci Caching AI skill do?

Cache Playwright browser binaries in CI/CD pipelines (GitHub Actions, Azure DevOps) to avoid 1-2 minute download overhead on every build.

Why use Playwright Ci Caching on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Aaronontheweb/dotnet-skills/tree/master/skills/playwright-ci-caching. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Playwright Ci Caching?

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 Ci Caching?

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

Is the Playwright Ci Caching AI skill free?

Yes. It is published on GitHub by Aaronontheweb under the MIT 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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