agentleFS
pauloribeiro16pauloribeiro16/my-skills/webapp-testing/SKILL.md

webapp-testing

Skill1 starsChanged 6 months agoMITView on GitHub

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs. Language-agnostic: the harness runs on Python + Playwright but drives apps written in any framework.

196 other projects use a version of this, 165 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use academy-guide, skill-share and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • AnthropicSkill

    academy-guide

    Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

    Also in 8 projects that use this

  • ArogyaReddySkill

    skill-share

    A skill that creates new Claude skills and automatically shares them on Slack using Rube for seamless team collaboration and skill discovery.

    Also in 23 projects that use this

  • SKB3002Skill

    intelligent-routing

    Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions.

    Also in 5 projects that use this

  • ArogyaReddySkill

    raffle-winner-picker

    Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

    Also in 26 projects that use this

  • zephyrwang6Skill

    topic-collector

    AI热点采集工具。从Twitter/X、Product Hunt、Reddit、Hacker News、博客等采集AI相关热点内容。当用户说"开始今日选题"、"采集热点"、"看看今天有什么新闻"、"今日AI热点"时触发。聚焦领域:Vibe Coding、Claude Skill、AI知识管理、AI模型更新、AI新产品、海外热点。

    Also in 4 projects that use this

  • zephyrwang6Skill

    deepl

    Übersetzt Texte, Dokumente und XLIFF-Dateien via DeepL API. Verwende für Übersetzungen mit /deepl translate, /deepl file oder /deepl xliff.

    Also in 4 projects that use this

  • +4 more from zephyrwang6
  • +1 more from ArogyaReddy

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 190 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Wait for page.wait_for_load_state('networkidle'): before inspecting the DOM on dynamic apps — otherwise you see the pre-JS state.

    line 29
  2. Very specific:

    Use sync_playwright() for synchronous scripts.

    line 87
  3. Very specific:

    Add appropriate waits: page.wait_for_selector() or page.wait_for_timeout().

    line 88

“Common” is measured: kept by at least 6 in 10 of the 190 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Tests local web applications by writing native Python Playwright scripts. The test harness is Python + Playwright; the app under test can be anything (React, Vite, Next, plain HTML, etc.).

When to Use

  • Verifying a local dev server actually serves the expected UI.
  • Driving end-to-end interactions against a page (clicks, form fills, navigation).
  • Capturing screenshots, console logs, or network failures for diagnosis.
  • Cross-checking a fix before handing control back to the user.

When NOT to Use

  • A page errors on load → web-debug (this skill expects a working page).
  • Aesthetic / visual quality → frontend-design or web-frontend agent.
  • Unit-testing pure functions → write those in the project's own test runner.
  • Production/CI workflows → this skill is local-dev-only.

Hard Rules

  1. Run scripts with --help first to see usage; do not read the source until you have tried running the script and found the defaults insufficient — these scripts are large and pollute context when ingested.
  2. Use bundled scripts as black boxes — scripts/with_server.py exists to be called, not read.
  3. Always launch chromium in headless mode — this is a dev tool, not a user-facing browser.
  4. Always close the browser when done — browser.close() (or with sync_playwright() block).
  5. Wait for page.wait_for_load_state('networkidle') before inspecting the DOM on dynamic apps — otherwise you see the pre-JS state.
  6. Put ad-hoc verification scripts under <project>/tmp/, never in the project's tests/ or root. Scratch does not become a deliverable.
  7. Use descriptive selectors — text=, role=, CSS, or IDs — because position-based selectors break the moment layout shifts.

Examples

Single-server automation:

python scripts/with_server.py --server "npm run dev" --port 5173 \
  -- python your_automation.py

Minimal script body:

from playwright.sync_api import sync_playwright

with sync_playwright() as p:
    browser = p.chromium.launch(headless=True)
    page = browser.new_page()
    page.goto('http://localhost:5173')
    page.wait_for_load_state('networkidle')
    # ... your automation logic
    browser.close()

Reconnaissance-then-action (server already running):

page.goto(url); page.wait_for_load_state('networkidle')
page.screenshot(path='/tmp/inspect.png', full_page=True)
content = page.content()
page.locator('button').all()
# then act on discovered selectors

Decision Tree: Choosing Your Approach

User task → Is it static HTML?
    ├─ Yes → Read HTML file directly to identify selectors
    │         ├─ Success → Write Playwright script using selectors
    │         └─ Fails/Incomplete → Treat as dynamic (below)
    │
    └─ No (dynamic webapp) → Is the server already running?
        ├─ No → Run: python scripts/with_server.py --help
        │        Then use the helper + write simplified Playwright script
        │
        └─ Yes → Reconnaissance-then-action:
            1. Navigate and wait for networkidle
            2. Take screenshot or inspect DOM
            3. Identify selectors from rendered state
            4. Execute actions with discovered selectors

Best Practices

  • Use sync_playwright() for synchronous scripts.
  • Add appropriate waits: page.wait_for_selector() or page.wait_for_timeout().
  • Report what was run, what passed, and what was skipped — never claim success without having run it.
  • Clean up tmp/ after the task — no leftover scratch files.

References

  • examples/element_discovery.py — discovering buttons, links, inputs.
  • examples/static_html_automation.py — file:// URLs for local HTML.
  • examples/console_logging.py — capturing console logs during automation.
  • scripts/with_server.py — server lifecycle helper (run --help first).

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.